Snowflake Reviews

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.

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.

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.

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.

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.

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.

I use this solution to create a proof of concept. I also create training for companies on Snowflake.

It is a very easy-to-use solution. It is user-friendly, and its setup time is very less.

They have a new console, but I couldn't figure out anything in the new console. So, if I shift to the old console, I can figure out where to create the database schema and other things, but I have no idea where to go in the new console. That's one thing they can improve. I don't know why they created a new console to confuse. The old, classic console is much better.

I started using Snowflake three months ago. 

It is stable.

It is scalable.

It is so easy that I didn't have to look for technical support. Its documentation is amazingly simple.

I also use Databricks for proof of concept and training. I have used Databricks much longer than Snowflake. Both have their own pros and cons.

In terms of ease of use, UI, and setup time, Snowflake is good. I would rate Snowflake a nine out of 10 from these aspects. In terms of workload, Databricks has higher points. The underlying infrastructure is faster for Databricks, which is not the case with Snowflake. Snowflake is a cloud database. So, in terms of processing power, Databricks has an advantage over Snowflake. Databricks is more suitable for larger workloads, whereas, for a regular or typical data warehouse that you want to run on the cloud, Snowflake is more suitable. 

Its setup was easy. You can create a connection and be up and running within half an hour.

I set it up myself.

I have not been billed yet, but it should be less. I'm still running the trial version, but it seems to be less than Databricks.

You must try it out. It is a wonderful product. I would also recommend trying out other products, such as Yellowbrick, and doing a comparison. Redshift has also come up with some serverless options. BigQuery is also there. BigQuery is as easy as Snowflake. So, my recommendation or advice is to try out these things and then pick the one that suits you. I don't have any bias towards any of the products. I have an impartial opinion about all the cloud data warehousing products.

I would rate it a nine out of 10.

We are silver or gold partners. The main use case is that we are building a data lake. We are creating a couple of downstream applications as well that will be used by data scientists. So, we will have a single data lake that will be used across the organization by different business domain users. The data is multi-source. We have data from SAP, JDE, and some Excel files.

The speed of data loading and being able to quickly create the environment are most valuable. 

For data, it provides built-in security and compliance with different standards, such as SOC 2, ISO, etc. So, we don't have to do a separate audit for compliance.

There are some gray areas. For example, there is no clarity on where the data sits exactly. That is their proprietary information, and they are not sharing those details. 

Its price should be improved. On the cost-side, it is more expensive than others.

If they could bring in some tools for data integration, it would be really great.

I have been using this solution for almost two and a half years.

It is pretty stable. Its stability is excellent.

It is scalable. As of now, there are 500 users, but slowly, we are planning to roll out to multiple regions. It is currently in Europe, and we will be rolling it out to the APAC and USA regions. By the year-end, there will be more than 1,000 users.

They're perfect. They're excellent. It could be because we are partners.

It is straightforward. It is not that complex.

Our own team deploys it for customers, but the initial configuration is done only by the Snowflake team because that is their area. 

I have worked with multiple clouds, and cost-wise, it is a bit costlier than others, such as Redshift. Its price should be reduced.

I would rate it an eight out of 10.

My company wanted to have all our data in one single place and this what we use Snowflake for. Snowflake also allows us to build connectors to different data sources. The ultimate goal is to provide reporting and analytics to all departments in the company.

This solution could be improved by offering machine learning apps. 

We have used this solution for one year. 

This is a stable solution. 

This is a scalable solution. 

Before Snowflake, we used Azure.

I worked with a Microsoft partner to set up the entire thing. This took three months. 

We have not yet experienced ROI. 

Overall, this is a helpful tool with a friendly interface. 

I would rate this solution an eight out of ten.

The most valuable feature is the clone copy.

In a future release we would like to have a link which would allow us to connect to an external database and create certain views in your own database. This is because it is becoming hard for us to compare the data between multiple sources.

I have used this solution for two years.

This is a stable solution. 

This is a scalable solution. 

The technical support of Snowflake is good. 

Positive

We have seen ROI when using Snowflake based on the insights we get.

I would recommend the SaaS version for their organization. It is not complicated to use. Establishing a private link with current cloud services has been challenging so I would recommend having some kind of a block.

I would rate this solution a nine out of ten. 

My current client is migrating from an on-premise data warehouse to the cloud, and they need to consolidate the data lake. I'm using Snowflake to develop the data lake and build data bots for certain functionalities. I've also used Snowflake to aggregate and clean data for my client's analytics.

I like Snowflake's data exchange capabilities. It can exchange data with downstream systems and other vendor partners as well.

There are some challenges with loading unstructured data and integrating some message queues or brokers. In one project, we had a problem connecting to one of the message queues and we had to take a different route altogether on Microsoft Azure. 

I started using this product about two years ago at my last company. Now, I'm a registered Snowflake partner, so working with Snowflake for one of my clients.

My clients haven't faced many stability challenges. It is a relatively new product that's still evolving. They're using it mainly for POCs, so they haven't faced any problems. 

The most valuable aspect of Snowflake is its scalability. The volume of data, which I have seen across almost in terms of five terabytes and other terabytes of data, I didn't see issues.

Snowflake technical support is good. At my previous company, they had a customer success officer for critical accounts, and they were accessible. When I registered as a partner, I also got a quick response from support. I would rate their support eight out of 10.

Positive

Setting up Snowflake isn't complex. I've not seen any challenges.

They have different pricing structures based on data usage. I think they have three or four tiers you can scale through. Most of the clients see an advantage from this type of licensing. That's the reason they go for it. It's priced competitively with other solutions.

I rate Snowflake eight out of 10. 

I use it for data warehousing. I just design databases, put data in there, and get data out.

Although I haven't used it much, it is very fast and the performance is great.

It has some technical quirks that whoever is using it needs to be aware of. It doesn't enforce typical relational database constraints. If you're not aware of that, you can really put some bad data in there.

I've been using it for about three months.

I would give it a ten out of ten. I haven't seen it failover.

I've never had any issues with it. It is being extensively used. We have between a hundred and a thousand users using Snowflake.

I have not had any experience with customer support, but I've heard it's good.

I've heard it's quite expensive.

I would give Snowflake a seven out of ten.

We use the product as a data warehouse.

The tool is very easy to use. The solution’s desktop features are also very easy to use. Also, the product’s SQL-based connectivity is also good. It can connect with any tool.

Snowflake needs to improve its programming part. Though the tool has Snowpath, it doesn’t support all features like its competitor, Databricks. Snowflake doesn’t support external data ingestion capabilities. You need to have third-party tools for that. Also, the tool needs to incorporate data integration features in its future releases.

I have been working with the solution for two years.

The solution is stable.

The product is scalable. You can scale the solution’s computation and storage features separately.

My company is a direct partner of the product. We have a lot of Snowflake experts who can resolve any doubts. Hence, I haven’t felt the need to contact customer service and support.

The solution’s setup is easy since it's a SaaS product. The tool’s deployment is fast and wouldn’t take more than two minutes.

Snowflake’s pricing is transparent. It is one of the cheapest cloud database warehouse providers. The tool follows a credit cost model. Everything on Snowflake is charged on the basis of credits. The credits depend on the cloud region and the public cloud provider that we use. Hence, the cost per credit will be different for AWS in Frankfurt and AWS in India. I think North Virginia is the cheapest region in terms of cost per credit. You will be consuming around 16 credits for large data warehouses.

I would rate the solution a nine out of ten. Snowflake is the market leader in data warehousing and cloud database. I don’t think that it has a direct competitor. I would suggest you give Snowflake a try if it fits your use case. You can open up a trial version for 45 days and convert it to a regular account. There are different tiers in the solution like business critical, standard, etc. The tool gets updates every week.