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Snowflake OverviewUNIXBusinessApplication

Snowflake is the #1 ranked solution in our list of top Data Warehouse tools. It is most often compared to Microsoft Azure Synapse Analytics: Snowflake vs Microsoft Azure Synapse Analytics

What is Snowflake?

Snowflake provides a data warehouse built for the cloud, delivering a solution capable of solving problems for which legacy, on-premises and cloud data platforms were not designed.

Snowflake is also known as Snowflake Computing.

Snowflake Buyer's Guide

Download the Snowflake Buyer's Guide including reviews and more. Updated: October 2021

Snowflake Customers

Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops

Snowflake Video

Pricing Advice

What users are saying about Snowflake pricing:
  • "The whole licensing system is based on credit points. You can also make a license agreement with the company so that you buy credit points and then you use them. What you do not use in one year can be carried over to the next year."
  • "Snowflake goes by credits. For a financial institution where you have 5,000 employees, monthly costs may run up to maybe $5,000 to $6,000. This is actually based on the usage. It is mostly the compute cost. Your computing cost is the variable that is actually based on your usage. It is pay-per-use. In a pay-per-use case, you won't be spending more than $6,000 to $7,000 a month. It is not more than that for a small or medium enterprise, and it may come down to $100K per year. Storage is very standard, which is $23 a terabyte. It is not much for any enterprise. If you have even 20 terabytes, you are not spending more than $400 per month, which may turn out to be $2,000 to $3,000 per annum."
  • "There is a separation of storage and compute, so you only pay for what you use."
  • "It is per credit. It has a use-it-as-you-go model. We bought a chunk of 20,000 credits, and they were lasting us for at least a year. We didn't have the scale of data like a much larger company to consume more credits. For us, it was very inexpensive. Their strategy is just to leverage what you've got and put Snowflake in the middle. It doesn't make it expensive because most of the organizations already have reporting tools. Now, if you were starting from scratch, it might be cheaper to go a different way."

Snowflake Reviews

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JH
Vice President of Business Intelligence and Data Engineering at a comms service provider with 201-500 employees
Real User
Top 5
Fast, convenient and requires almost no administration

Pros and Cons

  • "The thing I find most valuable is that scalability, space storage, and computing power is separate. When you scale up, it is live from one second to the next — constantly available as you scale — so there is no downtime or interruption of services."
  • "Maybe there could be some more connectors to other systems, but this is what they are constantly developing anyway."

What is our primary use case?

We needed a data warehouse and we made a decision on what is the right tool for us as a data warehousing tool by comparing products. We looked into Microsoft Azure, Red Shift and Snowflake. In the end, we decided on Snowflake because it looks more up to date, it seemed much better purposed as a data cloud solution.

It was developed from scratch and dedicated to being used on the cloud and that was what we were looking for. It was not just an on-premises system which was then converted to use on the cloud. It was completely developed from scratch and purely focus on the cloud.

Because it was programmed with that dedication, it has some significant advantages.

What is most valuable?

The thing I find most valuable is that scalability, space storage, and computing power is separate. When you scale up, it is live from one second to the next — constantly available as you scale — so there is no downtime or interruption of services.

It has something like a time machine, as it is from Apple it incorporates that feature in a way similar to their operating system. So whenever you need a version of the data to test with, you can just go back and take a copy of what was backed up yesterday. It makes some things very easy. It backs up your data warehouses, so for example in our case, a colleague deleted a complete database and we just need to do an undrop on the database and the data was there again.

This helps you to have a development environment with current data. You can just clone your production environment and you have a development environment. Everything you do you can test it on real production data without destroying the production data itself.

These are significant advantages.

What needs improvement?

The company is constantly working to improve the product. Now they have a focus on data sharing, which is really great. We already share data with others who do not have Snowflake. That alone is already great. But if the other counterparts also have Snowflake, then it is extremely easy to share data. You can control access at low levels and even on the cell level. It is very secure.

With the improvements they continue to make, there is nothing now that I would say I miss or features that need to be added. Maybe there could be some more connectors to other systems, but this is what they are constantly developing anyway.

For how long have I used the solution?

We have been using this product for two years.

What do I think about the stability of the solution?

The product is very stable. We never had an issue with stability. It is reliable and it is extremely fast. For example, we had a stock procedure that took half an hour to complete on our SQL cluster, and in Snowflake it was running in two minutes. So that is a significant time savings for just one task.

What do I think about the scalability of the solution?

The number of people at our company currently using the solution depends on what we are trying to accomplish. We have four developers in Snowflake and then we also have users who are leaving data with us for our further analysis. That may be around ten other users.

With the growing data set we have and the increase in the size of our business, we will increase the use of Snowflake, but not with respect to the number of users. We are a small company and all the users who need to use it are already using it. We have more data that we need to load and which we want to integrate before we will make more usage of Snowflake.

How are customer service and technical support?

There is nothing for us to complain about when it comes to technical support. The response time is really great. Whenever we have an issue there is some delay because they are in San Francisco in the United States so there is a time difference. But when we raise an issue, we get answers immediately. We may not get the solution immediately, as that is not always possible. But we get some type of immediate response and days later we have a solution. The tech support is quite responsive.

Which solution did I use previously and why did I switch?

We use several products together for our framework. We have our data warehouse which is in Snowflake, we use Domo for standard reporting and we use R for data science analysis.

Before we had Snowflake we had a different solution. We switched to Snowflake because we felt the need to modernize our data warehouse architecture. We were also thinking about having other solutions in the cloud to reduce administration costs. With no effort on our part, we could have a stronger system compared to the effort and cost of doing a similar thing on-premises. This was the biggest advantage of Snowflake. We really do not need to have those administrative efforts anymore. Now we don't take care about when we run out of storage or that we need to buy better CPUs because if we need more computing power, we don't worry about it, we just use it and it is there.

How was the initial setup?

The setup for the product was straightforward. For us, it was a little bit of a challenge because when we implemented the data warehouse, we also changed the architectural concept and we implemented a better framework. Because this framework was new to us it complicated our installation. But Snowflake itself, if you want to use and you have a data warehouse already in place with the right framework, then it is straightforward. You just store your data in and that's it. What you use on top is material for orchestrating all the load jobs. But this is other integrations and other choices that are really outside Snowflake itself.

The initial deployment from purchase until it was up and running in production took two months.

What about the implementation team?

We had a consulting company help us for the initial two months of the setup and then afterward we did everything by ourselves. We were quite satisfied working with the consultants and they helped us to implement quickly. We mainly needed them because we implemented this metadata framework. In the beginning, we had this consultancy for analyzing our platform, which to select and which tools should be used. After we completed this initial portion of the project over the two months, we needed them mainly for completing the implementation of the metadata framework.

Snowflake itself is easy to learn. If you know SQL it is really not very hard. Everything is well documented and it is not a problem.

What's my experience with pricing, setup cost, and licensing?

The whole licensing system is based on credit points. That means you commit to using it and you pay for what you use. You can also make a license agreement with the company so that you buy credit points and then you use them. So if you buy credit points that you think will last you for a year, you pay a certain amount of money and then you have these credit points available. What you do not use in one year can be carried over to the next year and it is that easy. The advantage of buying more is that you get a discount when you buy a bigger package with more credits.

What other advice do I have?

There is not really much advice I can give people considering this solution except that they should use it and enjoy it. It really sounds simple but that is it. Of course, you need to be careful with the usage of your credit points. Because there are so many possibilities in configuring the way you build your data warehouse or infrastructure, the data warehouse might seem logical, but it is not the best with respect to using credit points. You need to be careful about this. It probably takes half-a-year experience and then you will know how to do it. If you don't know what you are doing, Snowflake also helps to optimize your usage so that you do don't use too many credits points. After one year, we realized we had spent a huge number of credit points and we talked to Snowfake and then they came to us and we analyzed our systems together and we optimized the usage.

On a scale from one to ten where ten is the best, I would rate Snowflake as at least nine. Why not a ten is only because maybe there is something better on the market which is a ten that I don't know about. For me, it is already a ten.

Which deployment model are you using for this solution?

Private Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.
SreenivasanRamanujam
Director -Data Architecture and Engineering at Decision Minds
Real User
Top 10
Good usability, good data sharing and elastic compute features, and requires less DBA involvement

Pros and Cons

  • "Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."
  • "Portability is a big hurdle right now for our clients. Porting all of your existing SQL ecosystem, such as stored procedures, to Snowflake is a major pain point. Currently, Snowflake stored procedures use JavaScript, but they should support SQL-based stored procedures. It would be a huge advantage if you can write your stored procedures using SQL. It seems that they are working on this feature, and they are yet to release it. I remember seeing some notes saying that they were going to do that in the future, but the sooner this feature comes out, it would be better for Snowflake because there are a lot of clients with whom I'm interacting, and their main hurdle is to take their existing Oracle or SQL Server stored procedures and move them into Snowflake. For this, you need to learn JavaScript and how it works, which is not easy and becomes a little tricky. If it supports SQL-based procedures, then you can just cut-paste the SQL code, run it, and easily fix small issues."

What is our primary use case?

For Snowflake, we had four main use cases. The first use case was related to a data warehouse, and my banking client wanted to move his SQL Server database to Snowflake. All the source systems were also on Oracle and file-based systems, and the target data warehouse was SQL Server. From SQL Server, the client wanted to move to Snowflake. 

The second use case was related to a chat or messaging client. They were using EMR Hadoop as their data warehouse, but it was not performing, so we had to move the EMR Hadoop to Snowflake. 

The third use case was related to a ServiceNow compliance system, where ServiceNow was using SAP HANA for its reporting data warehouse, but it was too slow. It was not performing, and it was causing a lot of problems. We moved that ServiceNow compliance system from SAP HANA to Snowflake.

The fourth use case was related to a huge SQL Server database for a banking client. We moved the entire SQL database to Snowflake. 

What is most valuable?

Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. 

It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake.

Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake.

What needs improvement?

Portability is a big hurdle right now for our clients. Porting all of your existing SQL ecosystem, such as stored procedures, to Snowflake is a major pain point. Currently, Snowflake stored procedures use JavaScript, but they should support SQL-based stored procedures. It would be a huge advantage if you can write your stored procedures using SQL. 

It seems that they are working on this feature, and they are yet to release it. I remember seeing some notes saying that they were going to do that in the future, but the sooner this feature comes out, it would be better for Snowflake because there are a lot of clients with whom I'm interacting, and their main hurdle is to take their existing Oracle or SQL Server stored procedures and move them into Snowflake. For this, you need to learn JavaScript and how it works, which is not easy and becomes a little tricky. If it supports SQL-based procedures, then you can just cut-paste the SQL code, run it, and easily fix small issues. 

For how long have I used the solution?

I have been using this solution for three years.

What do I think about the stability of the solution?

So far, with all four clients who have this solution, I have not seen any problem that stands out and causes major headaches or something like that.

What do I think about the scalability of the solution?

Its scalability is really good. You can scale in both ways. You can actually scale up and down or scale out. Scaling up and down is done where we have an extra small warehouse, and we are moving to small, medium, large, or something like that. If you have a query that is running slow or a lot of data you are dealing with is slow, you can scale up. If you want to scale down from large to small, you can do that. 

If you want to get concurrency, scale-out architecture is available. I can actually do a cluster-based architecture where I can have two clusters, three clusters, or something like that. This way the concurrency can be improved.

In terms of the number of users, we have around 200 users.

How are customer service and technical support?

They have a website where you have to go and raise your tickets. They resolve the ticket, and they are working fine. 

They don't actually entertain emails nowadays because the company has become big. I remember initially interacting with them through email. Now they don't do that. They clearly say not to send emails and go through the ticketing process, which makes sense. For a big company, it is not possible to track emails.

How was the initial setup?

It is not complex. It is straightforward. It is a very simple database anyway. It is just having a script and running them. 

The only thing is that you have to go through the whole nine yards of getting an account or getting your single sign-on enabled. That is a part of every process. For any single sign-on application, you will have to go through this process. 

You also need to involve the right people, such as the security team, infrastructure team, and networking team. When they are there, the setup becomes easier, and there are no problems.

For its maintenance, we have only two or three people. We have one DBA and one account admin. There is another DBA who will take a rotation. You don't really need a big team to manage this because it is all cloud. Management is not that heavy.

What's my experience with pricing, setup cost, and licensing?

Snowflake goes by credits. For a financial institution where you have 5,000 employees, monthly costs may run up to maybe $5,000 to $6,000. This is actually based on the usage. It is mostly the compute cost. Your computing cost is the variable that is actually based on your usage. It is pay-per-use. In a pay-per-use case, you won't be spending more than $6,000 to $7,000 a month. It is not more than that for a small or medium enterprise, and it may come down to $100K per year.

Storage is very standard, which is $23 a terabyte. It is not much for any enterprise. If you have even 20 terabytes, you are not spending more than $400 per month, which may turn out to be $2,000 to $3,000 per annum. 

Which other solutions did I evaluate?

When comparing it with SAP HANA, there is no one solution that fits all. Snowflake is useful if you have a SaaS-based product such as Salesforce, Workday, Anaplan, and Greenhouse. You can get the data from this type of SaaS-based system and ingest data.

SAP is born out of the entire ERP ecosystem. You have enterprise resource planning, and you have manufacturing, finance, and other systems. Big manufacturing industries usually implement ERPs because they want to do reporting, etc. SAP has this custom box stuff, and it is very difficult to get the data out of your SAP systems. So, you have to use SAP HANA. If you're not using the SAP systems, you don't really need SAP HANA. You are free to go for Snowflake. If you have an ERP system and you need to get the data out and move into an SAP or ERP system, and you want to have a data warehouse actually of ERP system, then SAP HANA makes more sense because it can natively talk to SAP. In such a case, you don't want to go for Snowflake. 

What other advice do I have?

I would advise looking at your environment. Look at the workload and what you are trying to migrate. There is no one size fits all model. If you are a transaction system and you want to go with Snowflake, I would not advise this solution. If you are a reporting system and you want to migrate, Snowflake is the best choice. 

You also need to look at what kind of queries people are running. Don't assume that just because you are moving to Snowflake, you are going to cut down the cost by some factor. That is not going to happen. You need to really do a lot of homework and groundwork to know what kind of queries you're running and how can you avoid the compute costs. There is a lot of metadata available in Snowflake. You have to look at all that and then consciously try to improve the numbers. 

It is definitely a good tool and a good database without any adoption problems. Users who are SQL savvy can immediately adopt this solution. User onboarding is not really a huge exercise. It is a very simple exercise.

I would rate Snowflake an eight out of ten.

Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
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Learn what your peers think about Snowflake. Get advice and tips from experienced pros sharing their opinions. Updated: October 2021.
542,608 professionals have used our research since 2012.
VP
Solution Architect at a wholesaler/distributor with 10,001+ employees
Real User
Stable and scalable, enables us to share the data, and addresses the challenges of traditional data warehouses

Pros and Cons

  • "The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."
  • "They need to incorporate some basic OLAP capabilities in the backend or at the database level. Currently, it is purely a database. They call it purely a data warehouse for the cloud. Currently, just like any database, we have to calculate all the KPIs in the front-end tools. The same KPIs again need to be calculated in Snowflake. It would be very helpful if they can include some OLAP features. This will bring efficiency because we will be able to create the KPIs within Snowflake itself and then publish them to multiple front-end tools. We won't have to recreate the same in each project. There should be the ability to automate raised queries, which is currently not possible. There should also be something for Exception Aggregation and things like that."

What is our primary use case?

We are completely migrating to Snowflake, and we are in transition. It is primarily to combine all our data repositories into a single place. We have SAP BW and SAP HANA, and some of our business units have their own databases. We chose Snowflake to consolidate all of our data into a single place and then build enterprise data. We are then going to provide the data for our businesses in shared databases, on which they would do reporting. They will also have the ability to bring in their own data, which is currently not possible. They will also be able to do advanced analytics, machine learning, and AI in Snowflake, which is not fully possible on our current platforms. It will be used for all the operational reporting, such as sales, supply chain, appraising, and merchandising. We just started to do reporting related to sales and supply chain inventory.

We have its latest version. It is currently deployed on Amazon AWS, but we are moving to Google.

How has it helped my organization?

There are so many features that Snowflake offers to address the challenges that people have been facing in the traditional data warehouses for a long time. It allows us to have a single repository for all the data. Currently, we have data repositories all over the place, and we want to bring everyone onto one platform so that it can be utilized across the organization. Currently, we need database administrators and SAP administrators to manage multiple databases and platforms. With Snowflake, we don't need any admin, and there is zero maintenance. All we need is a platform architect who can just manage the Snowflake platform to create databases and security roles, and then you can share the data. By integrating everything into a single Snowflake platform, we have lowered the total cost of ownership quite a bit.

What is most valuable?

The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. 

Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities.

There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business.

What needs improvement?

They need to incorporate some basic OLAP capabilities in the backend or at the database level. Currently, it is purely a database. They call it purely a data warehouse for the cloud. Currently, just like any database, we have to calculate all the KPIs in the front-end tools. The same KPIs again need to be calculated in Snowflake. It would be very helpful if they can include some OLAP features. This will bring efficiency because we will be able to create the KPIs within Snowflake itself and then publish them to multiple front-end tools. We won't have to recreate the same in each project. 

There should be the ability to automate raised queries, which is currently not possible. There should also be something for Exception Aggregation and things like that.

For how long have I used the solution?

I have been using this solution for two years.

What do I think about the stability of the solution?

It is all cloud. It is really stable. We haven't seen any problems.

What do I think about the scalability of the solution?

We can scale up or down based on our needs. We don't have tons and tons of data, but based on the quality feedback from our vendors, it can handle large volumes and has the competency. With the dynamic scale-up feature, we are confident that it is going to meet all our requirements.

Currently, our number of users is very limited because we have just started the migration. We don't have many users on the platform. All of our focus is on Snowflake because we're moving to Snowflake, and its usage will increase in the future.

How are customer service and technical support?

I do not directly interact with the support, but I believe our platform architect reached out, and he got a response.

Which solution did I use previously and why did I switch?

We had SAP BW and SAP HANA as our main data platforms. We are slowly decommissioning SAP BW and SAP HANA and completely migrating to Snowflake. We wanted to have a single repository for all the data. The cost was also a factor.

How was the initial setup?

It is straightforward. To expose the data in the cloud, we had to go through our info security and legal, so that's the part that took time. After that is done, the process for setting up the platform, getting signed up with the initial free credits, and signing up the licensing for the credits was straightforward.

What about the implementation team?

We are working with a system integrator or vendor for this project. Our strategy is to work with an experienced vendor for the first project, and after that, we would be able to drive things forward.

Our experience with them is good. They're building the architecture of Snowflake. They have experience, and we have our own thoughts. We are working together and making sure that the architecture is for the long-term and not just for one project. Whenever we see that their focus is limited to the project, we are asking them questions to make sure that they are making the right decision.

In terms of maintenance, it doesn't require any maintenance, but you do require architects. We have three architects. One architect is responsible for the platform and takes care of creating security rules, grants, and users. We also have an integration architect who is responsible for data acquisition, ETL, and stuff like that. We have a data architect who is responsible for the overall data architecture in terms of what layers we need to establish and how do we model the data and publish that for consumption.

What's my experience with pricing, setup cost, and licensing?

There is a separation of storage and compute, so you only pay for what you use. 

What other advice do I have?

The key part is skill set because Snowflake is all SQL-driven data warehousing. Internally, we have some SAP BW development resources, and they need to learn and move on to understanding SQL-based coding and custom data warehousing concepts.

I would rate Snowflake a nine out of ten.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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Anirban Bhattacharya
Practice Head, Data & Analytics at a computer software company with 10,001+ employees
Real User
Top 5Leaderboard
Exceptionally good technology that addresses data warehousing challenges and is built and designed in a good way

Pros and Cons

  • "The way it is built and designed is valuable. The way the shared model is built and the way it exploits the power of the cloud is very good. Certain features related to administration and management, akin to Oracle Flashback and all that, are very important for modern-day administration and management. It is also good in terms of managing and improving performance, indexing, and partitioning. It is sort of completely automated. Everything is essentially under the hood, and the engine takes care of it all. As a data warehouse on the cloud, Snowflake stands strong on its ground even though each of the cloud providers has its own data warehouse, such as Redshift for AWS or Synapse for Azure."
  • "There are three things that came to my notice. I am not very sure whether they have already done it. The first one is very specific to the virtual data warehouse. Snowflake might want to offer industry-specific models for the data warehouse. Snowflake is a very strong product with credit. For a typical retail industry, such as the pharma industry, if it can get into the functional space as well, it will be a big shot in their arm. The second thing is related to the migration from other data warehouses to Snowflake. They can make the migration a little bit more seamless and easy. It should be compatible, well-structured, and well-governed. Many enterprises have huge impetus and urgency to move to Snowflake from their existing data warehouse, so, naturally, this is an area that is critical. The third thing is related to the capability of dealing with relational and dimensional structures. It is not that friendly with relational structures. Snowflake is more friendly with the dimensional structure or the data masks, which is characteristic of a Kimball model. It is very difficult to be savvy and friendly with both structures because these structures are different and address different kinds of needs. One is manipulation-heavy, and the other one is read-heavy or analysis-heavy. One is for heavy or frequent changes and amendments, and the other one is for frequent reads. One is flat, and the other one is distributed. There are fundamental differences between these two structures. If I were to consider Snowflake as a silver bullet, it should be equally savvy on both ends, which I don't think is the case. Maybe the product has grown and scaled up from where it was."

What is our primary use case?

It is used in my company as well as in my client's company. We are a system integrator, so naturally, we need to have the centers of excellence and competencies in Snowflake.

What is most valuable?

The way it is built and designed is valuable. The way the shared model is built and the way it exploits the power of the cloud is very good. Certain features related to administration and management, akin to Oracle Flashback and all that, are very important for modern-day administration and management.

It is also good in terms of managing and improving performance, indexing, and partitioning. It is sort of completely automated. Everything is essentially under the hood, and the engine takes care of it all. As a data warehouse on the cloud, Snowflake stands strong on its ground even though each of the cloud providers has its own data warehouse, such as Redshift for AWS or Synapse for Azure.

What needs improvement?

There are three things that came to my notice. I am not very sure whether they have already done it. The first one is very specific to the virtual data warehouse. Snowflake might want to offer industry-specific models for the data warehouse. Snowflake is a very strong product with credit. For a typical retail industry, such as the pharma industry, if it can get into the functional space as well, it will be a big shot in their arm.

The second thing is related to the migration from other data warehouses to Snowflake. They can make the migration a little bit more seamless and easy. It should be compatible, well-structured, and well-governed. Many enterprises have huge impetus and urgency to move to Snowflake from their existing data warehouse, so, naturally, this is an area that is critical.

The third thing is related to the capability of dealing with relational and dimensional structures. It is not that friendly with relational structures. Snowflake is more friendly with the dimensional structure or the data masks, which is characteristic of a Kimball model. It is very difficult to be savvy and friendly with both structures because these structures are different and address different kinds of needs. One is manipulation-heavy, and the other one is read-heavy or analysis-heavy. One is for heavy or frequent changes and amendments, and the other one is for frequent reads. One is flat, and the other one is distributed. There are fundamental differences between these two structures. If I were to consider Snowflake as a silver bullet, it should be equally savvy on both ends, which I don't think is the case. Maybe the product has grown and scaled up from where it was.

For how long have I used the solution?

I have been using this solution for close to three years. I kept a tab on Snowflake and its progress since it came into the market.

Which solution did I use previously and why did I switch?

Personally, I have worked extensively with Oracle, SQL Server, and Teradata. SQL Server has the Fast Track Data Warehouse (FTDW) appliance. Oracle has both the database and the appliance. I haven't worked on Parallel Data Warehouse, which is a big one offered by Oracle. Teradata is an appliance in itself. There is also Metadata. I haven't worked on DB2. 

All of these had their own lacunae. Data warehouses had their own problems. There were failures, challenges, and difficulties in adoption, and all of these have been addressed by Snowflake a big way. It has tried to marry the best of both worlds in terms of turnaround time, scalability, adoption, and seamlessness.

I hail from a classical data warehouse background. Snowflake has been kind of a silver bullet. It is trying to meet the best of both worlds. I wish I could do much more on Snowflake, but I'm tied up with many other things, which is why I'm not able to concentrate that much, but it is an exceptionally good technology.

How was the initial setup?

Its initial setup is very simple, which is its plus point. It is not at all a problem. You only need to understand a bit of the cloud ecosystem. When Snowflake is on Azure or AWS, you need to understand

  • What exactly is happening?
  • How these two are handshaking with each other?
  • What part Snowflake is playing?
  • How Azure or AWS is complementing it?

If these things are clear, the rest shouldn't be a problem.

What other advice do I have?

This could be something that might be debated upon, but Snowflake has two parts to it. One is the data warehouse itself, and the other one is the cloud. It is important to know about the cloud in terms of:

  • How a cloud functions?
  • How a cloud orchestrates through its services, domains, invocation of services, and other things?
  • How a cloud is laid out?

For example, let's take AWS. If AWS is invoking Lambda or something else, how will S3 come into the picture? Is there a role of DynamoDB? If you're using DynamoDB, how would you use it in the Snowflake landscape? So, cloud nuances are involved when we speak of Snowflake, and there is no doubt about that, but a more important area on which Snowflake consultants need to focus on is the core data warehousing and BI principles. This is where I feel the genesis of Snowflake has happened. It is the data warehouse on the cloud, and it addresses the challenges that on-prem databases had in the past, such as scalability, turnaround times, reusability, adoption, and cost, but the genesis, principles, and tenets of data warehousing are still sacrosanct and hold good. Therefore, you need the knowledge or background of what a data warehouse is expected to be, be it any school of thought such as Inmon school, a Kimball school, or a mix. You should know:

  • Data warehouse as a discipline.
  • The reason why it was born.
  • The expectations out of it in the past.
  • The current expectations.
  • What being on the cloud would solve?

These things on the data warehouse side need to be crystal clear. The cloud part is important, but it is of lesser essence than the data warehouse part. That's what I see, personally, and I guess that's the way the Snowflake founders have built the product.

As a data warehouse, I would rate Snowflake an eight out of ten.

Disclosure: My company has a business relationship with this vendor other than being a customer: reseller
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Mauricio Ruiz Falcón
Senior Information Management Architect at Raken
Real User
Top 20
I like how quickly the solution can be implemented

Pros and Cons

  • "The features that I have found most valuable are the ease of use, the rapidness, how quickly the solution can be implemented, and of course that it's been very easy to move from the on-premise world to the Cloud world because Snowflake is based on SQL also."
  • "It would benefit from an administration that allows you to be aware of your credit consumption once you have the service so that you may be sure how many credits you are consuming when you use the platform and to make sure that you are making the most efficient use of these resources. In other words, to improve their interface so that you may monitor the consumption of your credits on Cloud."

What is our primary use case?

We are a consulting company so our primary use depends on the niche that we are providing the services to and on which of the different versions they have. I think we are mainly using Snowflake Enterprise.

In general, it is being used for integrating information. Snowflake is a database platform, it gives information to support analytic needs, such as advanced data analytics like machine learning. In some of those cases it is also used for descriptive analytics, for instance BI.

How has it helped my organization?

One of example of how Snowflake has improved a client's organization is the democratization, it makes information available to more of the users.

What is most valuable?

The features that I have found most valuable are the ease of use, the rapidness, how quickly the solution can be implemented, and of course that it's been very easy to move from the on-premise world to the Cloud world because Snowflake is based on SQL also.

What needs improvement?

I think that the area of improvement with Snowflake is to improve the administration. It would benefit from an administration that allows you to be aware of your credit consumption once you have the service so that you may be sure how many credits you are consuming when you use the platform and to make sure that you are making the most efficient use of these resources. In other words, to improve their interface so that you may monitor the consumption of your credits on Cloud.

I also heard from a company we work for that it could be more user-friendly because it provides some tools but they are not user-friendly.

Additionally, it would be very helpful if Snowflake integrated machine learning and some other advanced analytics features within their language or product capabilities. Right now, they do it through some other company where you have to buy these capabilities from other vendors. There are some customers that don't have complex needs for machine learning or advanced analytics so they don't have to buy it from another vendor but can use it from the product itself if they have it.

For how long have I used the solution?

The whole company has been using Snowflake for about three years.

What do I think about the stability of the solution?

In terms of stability, so far it is very stable.

What do I think about the scalability of the solution?

Snowflake is very scalable. Our client companies where we implement Snowflake are medium to large sized. These companies have offices in different parts of the world, not just some regions, but companies with office users in different parts of the world. We are dealing with international companies. Their tendency is to increase the use of the Snowflake platform. It would serve all the analytical needs in these companies.

How are customer service and technical support?

I have not directly experienced the technical support. It's not part of my job to be involved on those kind of issues, but we constantly receive information as a partner from them and we are very in good touch with them and with the people we are working with, meaning the representatives that are within the Latin American market, which is where I work. They are very open and very fast with communication.

How was the initial setup?

The initial setup is easy. Full deployment takes a few weeks. The initial deployment for the first initiatives might take weeks. It's not complex, really. You may have it loaded after a full day and already providing results or interacting, but there are some other companies that have to be implemented to extract and consume the information from the database. But it's very easy.

Which other solutions did I evaluate?

There have been a couple of other solutions that we've been participating in the evaluation process of and some others that have been included in the decision process, including Redshift from AWS and also Azure Synapse from Microsoft.

For instance, AWS Redshift looked like it was easier to implement and to be adopted by the technical users, the programmers and database programmers. So far it has been far easier to adapt this technology. I'm not saying that AWS is a better technology. It's very complex, but at least what I've seen is that for them, it looks like it's been easier to use the first time.

We liked that Snowflake is able to be used as a multi-Cloud service - it can be used in AWS Cloud, Azure Cloud, or Google Cloud. Whereas AWS, or even Synapse, can only be used in their corresponding networks.

What other advice do I have?

I would definitely recommend Snowflake.

On a scale of one to ten, I would give Snowflake an eight.

I give it an eight out of 10 due to its room for improvement in the user interface for the monitoring of the credit consumption and that the user experience is not friendly. And also because the machine learning is lacking some advanced analytic features.

Which deployment model are you using for this solution?

Private Cloud
Disclosure: My company has a business relationship with this vendor other than being a customer: partner
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ES
AVP Enterprise Architecture at a financial services firm with 501-1,000 employees
Real User
Top 20
A perfect solution that delivers as promised and makes it easy to manage the overall ecosystem

Pros and Cons

  • "The overall ecosystem was easy to manage. Given that we weren't a very highly technical group, it was preferable to other things we looked at because it could do all of the cloud tunings. It can tune your data warehouse to an appropriate size for controlled billing, resume and sleep functions, and all such things. It was much more simple than doing native Azure or AWS development. It was stable, and their support was also perfect. It was also very easy to deploy. It was one of those rare times where they did exactly what they said they could do."
  • "Their strategy is just to leverage what you've got and put Snowflake in the middle. It does work well with other tools. You have to buy a separate reporting tool and a separate data loading tool, whereas, in some platforms, these tools are baked in. In the long-term, they'll need to add more direct partnerships to the ecosystem so that it's not like adding on tools around Snowflake to make it work. They can also consider including Snowflake native reporting tools versus partnering with other reporting tools. It would kind of change where they sit in the market."

What is our primary use case?

I have used it in my previous company. It was just a SQL server data warehouse using reporting tools on top of it. It was an on-premise SQL server environment, and it was a typical data warehouse use case, but we wanted to do things faster and more cost-effectively. 

We used it to modernize our data warehouse. We didn't want to invest more in on-premise servers, and we were looking for a way to quickly get more data joined together. 

How has it helped my organization?

It had definitely improved the way our organization functioned at the time.

What is most valuable?

The overall ecosystem was easy to manage. Given that we weren't a very highly technical group, it was preferable to other things we looked at because it could do all of the cloud tunings. It can tune your data warehouse to an appropriate size for controlled billing, resume and sleep functions, and all such things. It was much more simple than doing native Azure or AWS development. 

It was stable, and their support was also perfect. It was also very easy to deploy. It was one of those rare times where they did exactly what they said they could do.

What needs improvement?

Their strategy is just to leverage what you've got and put Snowflake in the middle. It does work well with other tools. You have to buy a separate reporting tool and a separate data loading tool, whereas, in some platforms, these tools are baked in. In the long-term, they'll need to add more direct partnerships to the ecosystem so that it's not like adding on tools around Snowflake to make it work. They can also consider including Snowflake native reporting tools versus partnering with other reporting tools. It would kind of change where they sit in the market.

For how long have I used the solution?

I have been using this solution for about three years.

What do I think about the stability of the solution?

We didn't run into anything. We had outages for a couple of seconds, but they were related to Amazon or AWS. They weren't related to Snowflake.

What do I think about the scalability of the solution?

We scaled it a little bit. We didn't have a lot of data to scale, as a lot of companies do. We only had a couple of terabytes of data, which is insignificant for a cloud platform. 

The development team had three or four people getting data in. Then report people were also using the platform, but they didn't really have to know that it was Snowflake because they were going at it through a reporting tool. There were probably 30 or 40 people writing queries against our reporting tools, which were, in turn, using Snowflake.

How are customer service and technical support?

They were really good. They were very responsive. There were never any issues with them. I would give them a ten out of ten.

Which solution did I use previously and why did I switch?

I've used a lot of different data warehousing solutions at different companies.

How was the initial setup?

It was easy as pie. In a couple of hours, it was up and running, and we were loading the data in. We had a fairly senior developer for that. He knew SQL server and queries very well. If you're used to developing in any type of SQL environment, you can jump in and use Snowflake really quickly.

What's my experience with pricing, setup cost, and licensing?

It is per credit. It has a use-it-as-you-go model. We bought a chunk of 20,000 credits, and they were lasting us for at least a year. We didn't have the scale of data like a much larger company to consume more credits. For us, it was very inexpensive.

Their strategy is just to leverage what you've got and put Snowflake in the middle. It doesn't make it expensive because most of the organizations already have reporting tools. Now, if you were starting from scratch, it might be cheaper to go a different way.

What other advice do I have?

If time to value is your primary goal, then I would recommend going for Snowflake over one of the other cloud providers.

I would rate Snowflake a ten out of ten. It is one of the few products in which everything demos well. It actually did everything they showed in the demos. We really couldn't find any gotchas in it. It kind of delivered as promised.

Which deployment model are you using for this solution?

Private Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.
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VG
Senior Vice President at a tech services company with 201-500 employees
MSP
Top 20
Good at autoscaling and has a nice time machine feature but they need to add a basic ETL framework

Pros and Cons

    • "It's difficult to know how to size everything correctly."

    What is our primary use case?

    We primarily use the solution for the data warehouse.

    What is most valuable?

    The solution offers everything you'd find on Azure or AWS. It has a lot of industry-standard features and capabilities.

    The product has excellent autoscaling. We can actually compute and scale-out at the same time without having to depend on other tools. You can do it on the fly, or within queries, etc.

    The Visual Copy Cloning is definitely one feature that everyone looks forward to due to the fact that it gives you regular backups. 

    The solution offers a very good time travel function that allows you to travel back in time to before your systems we corrupted. You can go back into your history and grab the last backup before corruption so that you regain almost everything you need. It gives you 90 days to fetch the data back if you need to. It's better than Azure options.

    What needs improvement?

    We've spoken with Snowflake about the fact that there are a few bare minimum requirements now these days for any data cloud, data lake, or platform. They've lacked a bit here, however, they're adopting some new measures that will be available in the next release, so that is sorted.

    Snowflake is partners with only AWS as a cloud platform. However, in India, Microsoft has got a big subscription. The product needs to be able to adapt to Azure a bit more in order to meet the local market demands. 

    It's difficult to know how to size everything correctly.

    They should incorporate at least a basic ETL framework.

    It's early days, however, I would put the solution at a seven out of ten. It needs a bit more time to mature. If I were to look at it strictly from a warehousing perspective, I'd rate it at an eight out of ten.

    For how long have I used the solution?

    I've been using the solution for about ten months. I started using it originally when we started our partnership with the organization.

    What do I think about the scalability of the solution?

    The one thing that seems to be unclear for Snowflake customers is the cluster sizing. No one seems ot know how to compute that.

    For example, if I'm running a warehouse that is extra small, as per my query performance, if I see like if this query will run perfectly on the machine I will have. However, I don't know which machine to go for. There's no direct comparison between an extra small, or a small, or a medium warehouse. I never get to know, unless I run the case query on different sizes, which to go for. It's hard to say "Buy only this and go for that particular size". Sizing seems to be a bit of trial and error. If they had some sort of benchmarking around their cluster size, that would be helpful.

    How was the initial setup?

    The initial setup is pretty straightforward. We didn't have any issues with implementation. It's not too complex.

    What's my experience with pricing, setup cost, and licensing?

    The pricing of the solution is fine. The storage is pretty cheap. They also offer a lot of discounts. The cost shouldn't really be a problem. 

    That said, the agreement should be more of a subscription basis instead of asking for a commitment. For example, Microsoft tells your the price and allows you to subscribe to that, whereas, Snowflake wants you to commit to a certain amount of time before they really give you firm pricing. 

    What other advice do I have?

    We're partners with Snowflake. We've been partners for just under a year at this point.

    I'd definitely recommend the product. It's worked quite well for us. 

    A new customer needs to understand, however, that they need a roadmap of at least five years when they are deciding on their data warehouse. They should compare costs and sizing to make sure they are getting the solution that makes sense for their current and future needs. 

    The solution integrates well with other applications, and if you need it to integrate with existing applications, you still should check to make sure it's possible.

    I wouldn't necessarily recommend Azure over Snowflake, as they aren't really a good comparison. Snowflake is more focused on data repositories and data warehouses. AWS does give you many options, however.

    Which deployment model are you using for this solution?

    Public Cloud
    Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
    AN
    Senior Data Engineer at a financial services firm with 10,001+ employees
    Real User
    The most efficient way for analytical intelligence reports to be sent to a customer

    Pros and Cons

    • "The most efficient way for real-time dashboards or analytical business intelligence reports to be sent to the customer."
    • "Their UiPath, the workspace area, needs some work."

    What is our primary use case?

    I use this solution for actively building out the cloud data warehouse and data platform for enterprise level customers as well as startups. Generally, our clients are looking for a data warehouse on the cloud to enable them to scale infinitely at a lower cost. I've worked for a finance analytical team building their data lake, the data platform on top of Snowflake, as well as for a telehealth team. It's basically about getting data from multiple sources and building out an entire data platform with data governance. We are customers of Snowflake. 

    How has it helped my organization?

    One small company I worked with had a MySQL RTS based instance and were using AWS RDS with MySQL on top of that. As a result they were unable to scale their database because there were around half a million queries being run per second as well as data querying and data updating. The migration to Snowflake helped the company because there are no limitations in the cloud and no longer restrictions on the queries. Performance for end users improved whether they were internal or external clients. They used to sell the data through APIs so this migration helped to grow their business overall as well as the ML team efficiency and the productivity of users who previously used the data platform. 

    What is most valuable?

    The most valuable feature of Snowflake is the query performance. Snowflake is the most efficient way for real-time dashboards or analytical business intelligence reports to be sent to the customer. There are a couple of areas where they have recently improved. One of the key features they introduced is an internal, table-based merch as well as storing of the unstructured data. You can now build a table out of unstructured data, metadata. This hasn't yet been officially announced.

    What needs improvement?

    Although the UI has improved lately, they still need to work on their UiPath, the workspace area.

    For how long have I used the solution?

    I've been using this solution for two years. 

    What do I think about the scalability of the solution?

    It's an infinitely scalable system, but if you use terabytes or petabytes of data, then you need to tune the levels. Each day, we get four to five gigs and overall, our data warehouse has 100 gigs plus, it's huge data. 

    Which solution did I use previously and why did I switch?

    Our clients previously used the RTS based MySQL and migrated to Snowflake from there. The primary reasons they moved was because of scalability and performance. Other than that, Snowflake reduces costs quite significantly. I also have experience with BigQuery which is particularly used for Google Cloud although these days they have a multicloud enrollment. Snowflake is vendor independent so you don't have to stick everything in Google Cloud. In terms of performance, Snowflake is faster than BigQuery. 

    How was the initial setup?

    The advantage of Snowflake is that it's easy to deploy and they take care of the setup. Basically, it's a cloud warehouse and doesn't need to be registered on any website. It's easy. It just requires dedicating space and registering. It shouldn't take more than a couple of days. 

    What's my experience with pricing, setup cost, and licensing?

    Snowflake is reasonably priced, close to half the cost of some other solutions. 

    What other advice do I have?

    In terms of performance the solution is good when compared to the analytical workloads and good in comparison to Redshift or BigQuery. The performance is on a slightly higher level, but when it comes to real-time performance, NoSQL is better than Snowflake, but that's in rare cases and depends on the particular requirement. Overall, for the analytical use case, Snowflake is a good solution and in terms of availability, it's a cloud data warehouse, so  they do replication and the like. 

    It's important to understand your business needs, because these tools need to be properly modeled and they have their own advantages. If you're new to Snowflake, it's worth starting slowly for one month and move gradually, because if it's a complex system and you move everything to Snowflake without good architecture, then you can get stuck with the original problem. It's worth taking the time to make it efficient and then design modeling; there are SnowPro certifications as well. 

    I rate this solution an eight out of 10. 

    Which deployment model are you using for this solution?

    Public Cloud
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
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