Snowflake Reviews

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.

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.

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.

I have been using this solution for two years.

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

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.

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

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.

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.

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.

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

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.

We have a data mart, and we are using it to share data with big enterprise customers with major security requirements.

Snowflake is an enormously useful platform. The Snowpipe feature is valuable because it allows us to load terabytes and petabytes of data into the data mart at a very low cost. Then we just share it out, and all the compute expenses are charged directly to our clients.

It would be better if they had a data profile tool that tells me where the gaps are in my time series data. We are anxiously waiting for them to release their data catalog and analytics capabilities, which is going to happen in June or July. If that works the way we think it might, then that would just extend our firm's capabilities into a space that we have never been interested in building ourselves. It could be a really good thing for us.

We started using Snowflake this year.

There's never any outage, and it's cross-cloud. The stability is not even a good question for that platform. It makes no sense to us.

Snowflake is scalable. It does cost more money, but it's some kind of magic they're doing behind the scenes that you don't have to think about. It's brilliant, and it's going to take over completely.

Their tech support is good. Their sales team is very technical, and they're able to speak to our engineers and walk them through what we need to do. 

About three years ago, Databricks was sort of the hot thing among our clients, and everyone was using it for low-code analytics. We had to deliver data in a format that was specific to Databricks. Databricks had this massive growth, use, and adoption. They have a very good footprint now, but we see those same clients shifting their data to Snowflake, and pretty much nobody asks for Databricks anymore.

I think there's this big war sort of brewing between Databricks and snowflake. Snowflake is going to come out with the analytics capability that Databricks has. They're working furiously to get it released. I don't know what it's going to look like, but they're going head-to-head with Databricks. I think Snowflake is going to crush them.

In the beginning, we didn't know what we were doing, and we racked up huge compute costs, shockingly and quickly. But the sales team was extremely helpful and showed us where we were doing everything wrong, and they explained to us how best to use their platform. We have massively funded data engineering teams, but now our use has plummeted to almost free.

Because of the caliber of our customers at the time, we had to sign on to the enterprise subscription tier. We're a startup, and we didn't know it at the time, but the cost per credit for the enterprise tier was almost double. 

The cost per credit, that's where you get all this unlimited autoscale that you don't even have to think about. We don't really need any of that because they already provide all the redundancy, backup, failover, and all of that stuff. We scaled down and cut all of our costs almost in half by getting rid of that scalability capability because we don't need that.

They give a different price for every single company. I don't know if I negotiated that well, but we got the enterprise tier for $3 a credit, and the other two were a dollar-ninety a credit. I suspect we don't have almost zero compute usage, but I know that our annual contract packages are below all of their minimums.

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

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.

We're running a POC to test scalability, performance, on-demand resource management, workload management, et cetera. The security aspect will also be important for us.

The product offers a lot of great features.

Architectural-wise, it's got great architecture. That's what we are looking for. It's kind of decoupled from storage and has virtual warehouses. We like that we can travel and keep things virtual. For us, the virtual warehousing is likely the most valuable aspect. You can spin up as many virtual warehouses that you want. That's quite useful as a feature.

I haven't found that the solution is lacking any features. It's quite complete.

I would like to see a client version of the GUI. Right now, it is a web GUI, which has stored the SQL, the worksheets. We are asking for that from Snowflake. We'd like to understand how can we save these worksheets on our local desktop. That is not there at this point.

I've been using the solution for about the past year as part of a POC.

In the past, we've used an SQL server. On the cloud side of it, we do have some experience. Snowflake, however, is the new data warehouse solution that we are looking into it.

If necessary, we may have to get into Synapse, and do a kind of a pilot project with that as well. We may evaluate them both to see which is better. We are not there yet. We are just working on Snowflake.

We are a direct customer and end-user.

We've been using the solution during a POC for the last year or so. It's a pilot project to test its feasibility for our company. We're just starting to get performance stats and stuff like that.

I'm not sure which version of the solution we are currently using. I don't recall the exact version number. Usually, people are running the latest version. Whatever the latest available option is is likely the number we are on.

I'd rate the solution at an eight out of ten. We're still in the POC phase, however, based on what we have seen, we are quite satisfied.

We implement this solution for our customers. It is a cloud data warehouse. It is SaaS, and it can be run on Azure, AWS, or something else. We are using its latest version.

It is a very good platform. It can handle structured and semi-structured data, and it can be used for your data warehouse or data lake. It can load and deal with any data that you have. It can extract data from an on-premises database or a website and make it available in the cloud.

It has very fast implementation and integration as compared to other solutions. There is no need for the DBA to manage or do the day-to-day DBA tasks, which is one of the greatest things about it.

In future releases, it can also support full unstructured data.

We have been using this solution for a year.

It is stable.

It has very good scalability. Your data can grow in the platform. We have at least 50 users of this solution in an organization.

Their vendor is wonderful. I only have good words for them.

It is not too complex. Its implementation is easy even for those people who don't know Snowflake and are coming from other environments, such as Oracle or SQL Server.

It can be implemented very quickly. Our customers in Israel implemented it very quickly. It was much faster to implement than other platforms.

It is on a monthly basis. It is based on your usage. There are no additional costs from the point of the licensing fee.

We do give some kind of evaluation to the customers about how much it is going to be. You can decide in Snowflake the virtual machine that you are using for customers. There are several kinds of virtual machines that you can use. It is similar to the clothing sizes: small to extra large. If you need more power in the coming month, you can decide in advance and take a more powerful machine. You can just select it from the platform. You can also decide which machine you want to take for extracting data.

I would advise others to check themselves how fast its implementation can be and how responsive it is. I would also recommend evaluating it before choosing other solutions, such as Microsoft Synapse or Amazon Redshift. You can test it yourself by using a test case. You can try to load the data on each platform, which can take a few weeks, but you will get to know the advantages of this solution. It is very different from other solutions.

I would rate Snowflake a nine out of ten.

We primarily use the solution to build some cost-effective solutions for a data warehouse, mostly for all non-transactional data.

The solution is very fast. It's not clunky or slow.

The product, overall, is quite inexpensive. It's very cheap to use.

The solution is extremely user-friendly and easy to navigate. The user experience is very good.

The initial setup is pretty straightforward. It's simple.

We found that the initial setup was pretty easy.

The solution has been stable and has provided good overall performance.

A company can easily scale the solution. It's not too difficult to pull off.

The technical support on offer is excellent. They're helpful for the most part.

There are always a few operation updates here and there that can be made. However, overall, there aren't any features or glaring shortcomings. It's pretty good. We can't complain.

While the solution is quite inexpensive, there is always a push from clients that want it to be cheaper in the future.

I have about six years' worth of experience with the product. I've been using it for a while. I'm comfortable with its aspects. I've used it over the last 12 months as well.

The stability is very good. There are no bugs or glitches. It doesn't crash or freeze. It's reliable. The performance is good.

The product scales quite well. If a company needs to expand it, it can do so without any problem.

We deal mostly with clients that have medium to large-scale organizations. It works well for both.

Technical support has been excellent. I'd rate them nine out of ten. They are knowledgeable and responsive. We are quite happy with the level of assistance we receive if we need help.

We've used a few other solutions including MySQL and a few other notable databases.

Right now, we are looking for some other options as well.

The initial setup is quite simple. It's a straightforward process. It's not overly complex. A company shouldn't have any issues with the implementation process.

We are implementors. We can implement the solution for clients if they need us to.

The product is very reasonably priced. It's quite cheap to use. It's less expensive than, for example, Oracle.

We are implementors of the solution.

We are using previous versions of the solution. It may not necessarily be the latest version all the time.

I'd advise other organizations to try it out and play with it a bit to see if it would fit their needs.

Overall, I would rate the solution at a nine out of ten. We've been mostly very happy with it.

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.

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

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.

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.

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

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

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.

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.

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.

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.

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.

It was only a workshop with training to know the tool. We were just testing the technology, and it was just a demo of the tool. We wanted is to connect switches with IoT and use Snowflake as an engine to process all the big data. It was on top of AWS, but our infrastructure is on top of the Google Cloud Platform.

The intention was to see if we can process on the front-end that we have. We have a console that processes a big amount of data. Instead of using BigQuery, we used Snowflake to see if it is cheaper than using BigQuery, but Snowflake wasn't cost-effective. In the end, we didn't go for this solution. We just saw how it can be implemented, but we never bought anything.

We don't have a metric, but I would say that the processing time was a key benefit and value-add. It provided on-time processing.

Its speed and performance were the most valuable. Easy configuration of Snowflake in any cloud was also a benefit.

Its pricing or affordability is one of the big challenges. Pricing was the only thing that we didn't like about Snowflake. In terms of technical features, it is a complete solution.

Its scalability is great. We have data processing of one terabyte per month.

It was not complex. Our implementation strategy was to put Snowflake on top of Google Cloud solutions instead of BigQuery, but BigQuery was better in price. So, BigQuery won in this case instead of Snowflake.

We got the guidance directly from Snowflake. They have a technical expert for Latin America.

We used Snowflake to see if it is cheaper than using BigQuery. It was just to maintain the cost or the KPI regarding the cost of connectivity by users. Snowflake wasn't cheaper than BigQuery, and its affordability was the main issue. 

My advice is to consider Snowflake when you have more customers. I wouldn't consider Snowflake until I have sufficient customers. 

Whether we will consider Snowflake in the future depends on how BigQuery behaves. If the cost of BigQuery starts increasing and becomes similar to Snowflake, we're going to switch. If not, we're going to remain with BigQuery. 

We might also consider other similar solutions, such as Yellowbrick, or switch to another cloud solution, such as Azure or AWS, depending on the price. Right now, we are paying about $2,000 per month. Our goal is to have the total cost of everything to be around $3,000 per month. It is more or less our goal for KPI kind of thing.

I would rate Snowflake an eight out of ten.