We use the solution extensively for reporting and analytics. We put data into it and publish reports. A report could be a dashboard. The data is used for data-driven insights and AI and MLOps. There are many use cases for the data that we procure on Snowflake.

The product has impacted collaboration across our teams. The correlation is quite easy. We use the solution because most of our life sciences and healthcare customers prefer it. Their preferences directly impact us as vendors and partners. We have to promote the same tools and technology they are familiar with.

The product is quite fast. There are several connectors in Snowflake that we could leverage for ingesting data. The data could be in zettabytes or petabytes. It is easily manageable.

The cost is a bit high. The storage cost and the extraction cost of data are high. The final invoicing cost will be higher if we do a rich data-oriented task on Snowflake.

I have been using the solution for close to three years.

The tool is stable and very powerful.

We have at least 1000 users in our organization. We will surely use the product in the future.

The solution is cloud-based. There is no on-premise solution. It has its own cloud. The installation is quite easy.

The solution is worth the money. It is good to use. It has a lot of features which are not available in other products. However, users must explore other products to control their costs.

Other products like Google Cloud, AWS, and Azure have competitive pricing. Snowflake costs 15 to 20% more than AWS and Microsoft Azure.

People who want to buy the product must initially use the free trial version. It can be installed on a desktop. The user can do a lot of R&D. We have a good playground. We can play with the components and learn them easily. We can learn how each component talks to each other, how the performance is, and how to create tables. There are a ton of tasks we can do.

After ingesting the data, we can perform advanced analytics and make models. The end users can do many things on the tool. It is quite an easy tool. I will advise any new user to install a free version. They will be able to learn about the product and get good insights when they work on their pilot project. Overall, I rate the tool a seven out of ten.

We use Snowflake as a database to store all the data we stream from the source system.

The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power. If I want to change the computation with other tools like Netezza, I would have to add a hard disk to it. With Snowflake, being on the AWS side, changing warehouses provides me with faster execution of my queries.

The real-time streaming feature is limited with Snowflake and could be improved.

Currently, Snowflake doesn't support unstructured data. With Snowflake, you need to be very particular about the type of data in your source systems. It has to be in a proper structure. You cannot push data to Snowflake in any possible way.

I have been using Snowflake for a couple of years.

Snowflake is a stable solution.

Around 400 users are using the solution in our organization.

We previously used IBM Netezza. We switched to Snowflake in 2020 because it provided us control over its scalability and costing model.

The solution’s initial setup is comparatively easier.

Snowflake is a cloud-based, scalable solution that provides strong data security. Handling all the data is much easier in Snowflake, and it has a very nice interface to control user access. The administration of Snowflake is also comparatively easier.

Snowflake is a cost-effective solution.

Choosing Snowflake completely depends on the quantum of data your organization has and the requirements. Snowflake is suitable for someone looking for a scalable and cost-effective solution that provides quick analysis.

Overall, I rate Snowflake a nine out of ten.

Snowflake is good for analytical purposes when you have a lot of historical or sales data that you need to release and use for different types of analysis, such as tracking sales and measuring the performance of your sales team and product.

The product's most important feature is unloading data to S3. It provides a single syntax query to analyze data directly from a database to an S3 bucket.

The product's performance could be improved.

I have been using Snowflake for a couple of months. We are using the latest version.

The product is stable.

We did not need to scale our Snowflake environment beyond what we needed. We have a fixed amount of traffic from a fixed number of clients. We know the load we need to handle, and based on that, our subscription is made.

Snowflake is cost-effective. The pricing is better than Firebolt. Firebolt is better when there is idle time. If we run Snowflake all the time, the cost will be higher.

We are working on two solutions for Snowflake, one for the cloud and one for on-premises. It has good documentation. If someone goes through it, they will quickly understand how it works. However, Firebolt's documentation is more comprehensive. If I need faster results, I'll prefer the Firebolt; if I need performance, I'll use Snowflake.

Overall, I rate it a nine out of ten.

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.

The solution is primarily used for data warehousing. 

It's a good tool. It is quite easy to manage. 

There are a lot of features. 

If you accidentally delete something, you can time travel and retrieve it. 

Within half an hour or even 15 minutes, you can set up a new data warehouse, and you can clone a table or whatever you like. 

It's easy to provide access to clients if they need to.

The solution is stable. 

It can scale well.

There is good online documentation via the community, and you can learn the solution on your own. 

These days, they are pushing users towards the GUI or graphical version. However, I am more familiar with the classic version. I'd like to continue to work with it using the older approach. That's just a personal choice. I prefer the database views like you would get on an SQL Server or other databases. 

I've been using the solution for two and a half years or so. I haven't used it for too long. 

The solution is stable and reliable. There are no bugs or glitches, and it doesn't crash or freeze. I've never had an issue when you connect it to your infrastructure. I'd rate the stability nine out of ten. 

We have 250 or more users on the solution currently. They are predominantly IT specialists, including engineers and developers. It's for those on the application side of development. The solution is scalable. I'd rate the scalability nine out of ten.

I've never directly dealt with technical support. We do have a direct contact. There are other people who might have. There might have been a version issue at some point. However, it wasn't something I dealt with. I've only interacted with the Snowflake community pages. 

We are currently moving everything from Oracle to Snowflake. 

We've used a combination of other tools in the past. We've used Microsoft's Stack, for example. We were using a SQL database in the past. 

We're migrating from Oracle right now. We have two people that handle the maintenance of the solution. A company may need two to four engineers to manage maintenance 24/7.

It's not difficult to deploy. It's pretty straightforward. It took us only a couple of minutes in order to get everything up and running. 

We pay a licensing fee to use the solution. It's paid monthly. My understanding is that it is not that expensive. We might have a specific extra cost surrounding running it on a private cloud. I'd rate the cost as six out of ten. It's moderately priced compared to others on the market. That said, I don't directly manage the account and don't directly deal with pricing. We have a contract of three to five years. 

I'm an end-user. 

Everything is on the cloud, and therefore I'm always using the latest version of the solution. It updates itself regularly. 

It fulfills our needs, and it's easy to pick up by looking at some reference guides. I'm still getting used to the GUI. I might find it even easier to use if I go through more formal training. Right now, I've simply learned it on my own. Overall, I'd rate the solution eight out of ten. 

We use the solution for data storage and integration purposes.

The solution's most valuable feature is path application.

They should improve the performance of the solution's transaction application.

It is a stable solution.

We have 20-30 solution users in our organization.

The solution's customer service is good.

The solution's initial setup was very straightforward.

The price for the solution's license depends on the use cases.

I recommend the solution to others and rate it as a nine. It efficiently processes the data and gets reports as well.

We use the solution to build the pipelines in stream sets, including data source, data warehouse, and destination endpoints.

The solution's most valuable features are storage, run time, scalability, and minimum query time compared to other vendors.

The solution's stability needs improvement.

I have been using the solution for seven or eight months.

Recently, I encountered an issue with the solution's data warehouse. The resource monitor had exceeded its quota. I rate its stability as an eight.

I rate the solution's scalability as a nine.

We use Hive and Hadoop as well. Snowflake is more stable and scalable.

The solution is more straightforward to use than the other IDBMS tools. It has a simple query process. Its computing time is less as well. One can easily have access to it. I rate it as a nine.

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.

Stable

Scalable

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.

We constantly monitor the usage with grafana dashboards to keep the ROI growing and to assist/ alert users about any wastage.

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. We're also happy with Google Big Query. 

Snowflake is growing with newer features and capabilities. But not much success with Stream lit app. Big query + app sheet is an alternative that we're considering.