Snowflake Reviews

I use the tool with visualization tools like Tableau and Power BI. We load the data into these tools and use them to build customer reports. We often need to write scripts to perform transformations before sending the data to the visualization tools.

The tool's performance is good. I think it's the best in the game right now. It usually charges per query. For example, if you run a SQL query on Snowflake with the same number of data records, it would take less than half the time compared to running it on Microsoft. It has good documentation. You can pick up Snowflake if you have previous knowledge of SQL.

I can only access Snowflake from the web. It would be better if we could have an app that we can install locally on our laptops to connect to the server without needing to go to the web page. Apart from that, it's hard to point out any limitations in the tool.

I have been working with the product for four years. 

The tool is scalable. I've used it for datasets with more than ten million records.

I only put data in and modify data. Most of the time, I don't require technical support. We occasionally had downtimes, and the data engineer would escalate these issues to Snowflake to resolve them.

The solution's deployment is simple. You purchase the license on the Internet—I think there's only a free trial for thirty days—and set it up like a Gmail account. It takes less than a minute to set up. You can set up your Snowflake server or use an enterprise vendor like AWS or Azure. Recently, Snowflake has been moving away from third-party vendors. They want to set up their remote infrastructure.

The tool's pricing is based on the number of queries you want on your database. The cost is small. To get the tool's pricing, you can do the math based on the cost per query, which is $0.002. If you're running your queries frequently, your charges will be higher than running fewer queries.

I would give Snowflake a ten out of ten in terms of performance and a nine out of ten in terms of scalability. I rate the overall solution a ten out of ten. 

Our primary use case for Snowflake is inputting data generated by AWS.

This solution has helped our organization by being easy to maintain and having good technical support.

The features I have found most valuable are the options to connect with extendable sources in three buckets in which we can also create stages.

I think that Snowflake could improve its user interface. The current one is not interactive.

I have been using this solution for about one year.

I would rate the stability of this solution a nine, on a scale from one to 10, with one being the worst and 10 being the best.

I would rate the scalability of this solution a 10, on a scale from one to 10, with one being the worst and 10 being the best. There are around five developers in our company and 500 end users for this solution.

We previously worked in AWS.

I would rate the initial setup process an eight, on a scale from one to 10, with one being the worst and 10 being the best.

I would advise other people trying to use this solution to build a skill balance as it's quite difficult to work in Snowflake.

I would rate this solution as a whole a nine, on a scale from one to 10, with one being the worst and 10 being the best.

We use the solution as a data warehouse for our financial services firm. 

The core feature of the platform is everything works, and that's what I like about it. Our time to market is faster, it requires less maintenance, and I can build and deploy a product exceptionally quickly.

Everything is automatic, and I don't have to do any maintenance.

I want tokenization, so they could either acquire a company that does tokenization or somehow integrate with one. If I could do tokenization in line with other development without having a third-party system, that would ease integration and security, of course.

More data governance and access control features would be a welcome addition.

We have been using Snowflake for about three and a half years. 

Snowflake is a stable platform. 

The power of Snowflake is that it scales automatically and indefinitely. We have around 500 internal users using the solution daily, and most of our applications use the product in some shape or form, so that's a few hundred thousand external users.

The support model is that we have a Snowflake rep, and if I need anything, I can reach out to him, and he can get people on board within minutes. The support is fantastic.

Positive

We weren't satisfied with our data warehouse, AWS Redshift, Oracle, and some on-prem elements such as a SQL Server. We wanted a cloud data warehouse that didn't require a lot of manual intervention and maintenance, DBAs and so on. We wanted a solution that could scale automatically and pay-as-you-go to cut down on wasteful infrastructure. Therefore, Snowflake made a lot of sense, plus compared to Redshift at the time, the separation of storage and computing was huge. That was an essential differentiator for us.

We previously used ThoughtSpot, specifically their Falcon engine, their appliance version, and it did everything on its own. We brought in Snowflake later when ThoughtSpot introduced their product called Embrace. We were among the earliest adopters to switch, and six to eight months after, we integrated with Snowflake.

The initial setup was straightforward; it was one of the easiest I've done, so I rate the solution five out of five for ease of setup.

We carried out the deployment in-house, and Snowflake is a SaaS solution, so setup was rapid. All we needed was some user account information. 

Snowflake is expensive, but when I consider what we get for that price, it's fair. I rate the solution three out of five for affordability, right in the middle. 

I rate the solution nine out of ten. 

Snowflake is ahead of the competitors because it's completely automatic and hands-off in terms of maintenance. Many of the competitor products have similar features to Snowflake, but what they call automatic still requires someone to understand it. If they give us 100 levers, somebody has to know what each of them does and when to pull them, whereas Snowflake is entirely hands-off.

My advice to potential customers is to have a team member who understands performance tuning and to figure out optimal credit usage ahead of time to avoid wasteful spending.

The implementation is essential because the solution provides a lot of power out of the box, and the initial configuration needs to be fit for purpose. If I have a relatively small use case where I don't need much power or don't have much data, the product needs to be configured for that. As opposed to an external case where I might need high power for a government job, for example, then the configuration needs to be scaled up.

The solution is very good for building data warehouses. However, it has some limitations if we need it for more use cases.

All the features of the product that are needed for the data warehouse are good. The solution enables the ingestion of data and the usability of preferred languages while creating the data. The performance of the engine is good. The solution speeds up the process of onboarding. We can connect to different sources and get the data very fast. 

The tool does a very good job in reporting and data transformation. We can adapt it well to our needs. When we try to ingest data from many sources, it helps harmonize the data sources. It also helps with duplication and cleaning of the data. It is a pretty difficult and time-consuming task, and Snowflake helps us with it.

I do not like the proprietary format of the solution. Getting data out of the tool to third-party applications is difficult. The data science workloads must be improved. Snowflake has a lot to learn. There are better options in the market for data science.

I have been using the solution for almost three years.

The tool is stable. I rate the stability a nine or ten out of ten.

If we need to scale up, it will impact our costs. I work in a consulting company. We have a department dedicated to Snowflake. We have seven to eight people on our team. Our clients were medium-sized businesses with 1000 employees. They are focused on data analytics solutions. They also have departments for Azure and AWS. I rate the tool’s scalability a seven or eight out of ten.

I rate the ease of setup a seven or eight out of ten. The tool is deployed on the cloud. The time taken for deployment depends on the workload and how we build it.

The solution is expensive. I rate the pricing a nine out of ten.

We are partners. The impact of the solution’s automatic scaling feature on the workload depends on how we build our workload. The vendor must take a look at the market and how technologies evolve. The solution can do more in the area of distributed systems. If our use cases require data scientists, I rate the tool a three or four out of ten. I rate the tool a nine or ten out of ten for SQL data warehouse use cases. Overall, I rate the product a seven out of ten.

Data warehousing is typically a rich guys' toy. Large enterprises are only able to leverage data warehouses for data analytics purposes. We wanted to change that and wanted to build a data warehouse template model for businesses across industries. 

If Snowflake was not around, we would have used Google's Big Query or Amazon's Redshift, or a MYSQL/Postgres database in a Windows VM (virtual machine). However, Snowflake made it a lot easier for us with loads of features such as encryption of data in motion and at rest, masking policies, time travel (to correct data load issues), controlled access based on roles, data sharing, third-party data from marketplaces, etc.

It helped us to build MVP (minimum viable product) for our idea of building a data warehouse model for small businesses. 

About ten years ago, force.com from salesforce.com offered a similar platform for us to build data warehouses. However, our staff with a data engineering background found it easier to build the data warehouse in Snowflake, with the easy-to-use SQL interface and RBAC models (role-based access control). The platform saved us money as it automatically shuts down the compute engines after about five minutes of idle time. Per second billing (above the first minute) is great. 

In my view, cost optimization for the computing power required by the ETL jobs, reports, and dashboards is the most valuable feature. Especially for startups, this helps us to keep cost spending within control without having to worry about manually shutting down the server when not used.  

As a Google partner, we like to leverage GCP (Google Cloud Platform). Snowflake supports GCP, AWS & Azure platforms. This works just fine for us. Encryption of data with multiple keys for both data in transit and data at rest gives us enough confidence to use snowflake for our customer 360 solutions.

Currently, we use Snowsight only to monitor the usage of the Snowflake environment by our users. However, if Snowsight can be improved, we can host our BI (business intelligence) environment also within Snowflake. In our case, to provide basic reports and dashboards, we started to use Tableau, Power BI, Looker, and Qliksense, depending on our customer preference.    

We are yet to figure out how to integrate tools, such as Liquibase, to release changes to our data warehouse model. If Snowflake could guide us with some easy-to-use integration (similar to DBT integration), that would be great.

I've used the solution since 2020.

Support can be enabled in the Snowflake UI.

Neutral

In the past, we used Google Cloud SQL. However, Snowflake offered cost optimization among the many other useful features. They also introduced app building on top of the data hosted. 

The initial setup is not difficult. Google Search will lead us to articles that can guide us on the setup of users, roles, warehouses, and access controls.

We did the initial setup on our own, and it was not difficult.

Many interesting features are available only in the enterprise edition. Check out the differences when you are evaluating the product: https://docs.snowflake.com/en/...

We considered MySQL and Google Big Query.

Snowflake is growing with newer features and capabilities. We're glad that we chose it. 

Basically, if at all, we wanted to have an interface for data warehouses on the cloud which worked on Azure or AWS. Snowflake, provides a more intuitive, rapid user interface where people can connect and maintain warehouses and share data among the people in the companies easily. Its pricing model and the model have made maintaining virtual warehouses simpler.

I appreciate the Snowflake marketplace, where you can drop data and allow other people throughout the world to access it. You can go to the Snowflake marketplace and connect to some data. If somebody else publishes, for example, COVID-19 data or weather data, you can sign up for new data sets and bring them into your warehouse, which I found very interesting.

You can connect to different cloud sources, including Azure and AWS. 

You can report out, and all the cloud technologies have connected to Snowflake, allowing you to move the data or get the data into Snowflake. 

The initial setup was pretty simple. 

It scales really well. 

The solution is stable. 

The solution is reasonably priced. 

I don't know about GCP, if they have connected for GCP. If they don't, they should allow for it.

Overall, they're doing great. I don't have any specific complaints or improvements that need to happen.

I've used the solution for a couple of years now. 

The solution is quite stable since everything is in the cloud, and the data these days has become cheap with storage and everything in the cloud. Through clusters and warehouses, sizes can be increased or decreased based on usage, and they can be turned on and turned off. Sustainability-wise, I think it's a pretty good solution.

It is scalable. The warehouses or auto-scaling features in the warehouses are great. You can go from small to medium to large all the way up to extra large, and there are different auto-scaling tasks that can happen. You can turn it on and turn it off based on the usage or auto-turn it on and turn it off. That's a pretty nice feature to have and we find it both sustainable and scalable for sure.

I work for clients, so last time when I worked for a client, there was a group of 100 people who were actually signed up to use Snowflake. 

I've never dealt with technical support. We did have people from Snowflake working with us directly, and we never ran into any issues that needed troubleshooting. The personnel from Snowflake, of course, would resolve whatever came up. 

I come from an Azure background as well, so Microsoft also comes with Azure Synapse, where it's a similar functionality as Snowflake, where it's warehousing on the cloud. Azure Synapse is also good. I'm unaware of AWS or GCP, and I heard that Google Cloud Platform also has Big Query and big data capabilities, which are tough competitors for Snowflake and other cloud warehousing tools.

The implementation process was pretty straightforward. I didn't set it up, though. I used an already set up version. I just had to connect. I had to push data from Azure to Snowflake, create tables there, and have data loaded into those tables, and that's it. I wasn't doing anything else, so I didn't work on the infrastructure of Snowflake.

You would need a group of two or three people to maintain the product.

I work for a consulting firm, so I don't work for the client, so I really don't know what the company used for deployment.

Licensing was based on the warehouse. I don't recall it being very expensive. 

I'm a consultant and end-user.

I'm not currently using the solution right now and do not recall the last version I was on. 

Now, I'm working for a different client on a different platform altogether. My company, as such, doesn't use Snowflake since we are in consulting. We have expertise in something, and then we help the clients deliver that solution on the technology.

Potential new users should just definitely give it a shot. They should start off with a POC, proof of concept, for the data that they have, and then, if everything works well and they can migrate in a cost-effective way. 

I would recommend Snowflake to start off with since it's just picking up over the last couple of years. If I have to recommend anything, however, it would be more Microsoft tools I would recommend since that all comes as a package. You can do Synapse and Azure Data Factory, which is  for ETL. You can also do Azure Data Lake Storage. There are different things that you can do when you buy something in a package like that. That said, I definitely recommend Snowflake if someone wants to give it a shot.

I'd rate the solution eight out of ten. 

We use this solution to ingest e-commerce advertising and web analytics data and completing an analysis. There are 60 people using this solution in our business. 

We are working with a TV advertising agency and they were able to set up a Snowflake data share to share ad spend with us and it was very quick to integrate.

The most valuable feature has been the Snowflake data sharing and dynamic data masking.

The cost efficiency and monitoring of this solution could be improved. It's easy to spend a lot on Snowflake and it does offer monitoring tools but they're pretty basic.

I have been using this solution for three years. 

This is a stable solution. 

This is a scalable solution. 

I would rate the technical support for this solution a four out of five. 

We previously used Amazon Redshift.

 The initial setup was straightforward.

We did have a consultant help us.

We do see a return on investment.

Pricing is based on usage. It is the most expensive of our data tools.

I would advise others to check costs when implementing any changes, such as new BI tools or a new data source. Set up different warehouses for your different tools so that you can track cost.

I would rate this solution a nine out of ten.

We're ingesting third-party data analytics into a database held within Snowflake. We have pre-production and production environments with integration to staging and production schemas.

It has improved the way our organization functions. However, we're still pretty elementary in our understanding of how it all works and the complete capabilities of Snowflake.

The adaptation to development languages is most valuable. Our developers can SQL code or something else. It has been convenient in that regard.

The data sharing capabilities across business units within the organization should be better. There could also be better integration.

I have been using Snowflake for a year and three months.

We have high confidence in it.

We have high confidence in its scalability. In terms of its users, for our solution, we only have a team of 10, but we have plans to increase its usage.

We haven't had any technical contact. All of it has been internal for our organization.

This is a net-new solution. So, it's brand new. We chose Snowflake for a variety of reasons, but mainly, we chose it for its scalability and data sharing capabilities.

I would rate it a three out of five in terms of complexity just because we didn't have any Snowflake developers that were available. The implementation took about three months.

We implemented it on our own.

We have not yet seen an ROI.

We're based on credits. So, we're paying four and a half dollars of credit. There are no additional costs. I would rate it a two out of five in terms of pricing.

I would advise ensuring that you have the expertise with domain knowledge in Snowflake. The time from initial concept to deployment could be expedited extremely fast. Just from our internal learnings, we see that our time to production has increased month over month.

I would rate it a six out of ten just because we're unaware or naive to the full capabilities of the product. However, I would highly recommend it in terms of setting up data warehousing internally over an Azure solution, such as Synapse, or something else.