Snowflake Reviews

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.

We're using it more for data warehousing and distribution.

Snowflake is a SaaS platform, so I'm using whatever is the latest version.

It's definitely for compute. The best use case of Snowflake is massive compute. With the parallel reads that we can do from Snowflake, we can combine data from disparate sources, consolidate it, and provide it to end clients through custom stored procedures.

It's user-friendly. It's SQL-driven. The fact that business can also go to this application and query because they know SQL is the biggest factor. So, we can provide all the data, and the analysts, data scientists, and product strategists can go and analyze the data themselves.

Room for improvement would be writebacks. It doesn't support extensively writing back to the database, and it doesn't support web applications effectively. Ultimately, it's a database call, so if we are building web applications using Snowflake, it isn't that effective because there is some turnaround time from the database.

I'd like them to look into the limitations of REST API. Snowflake came up with this native API concept, but it has got a lot of limitations. I'd like to see it provide better service-based APIs so that it can provide data as a service.

I've used Snowflake for over three years.

Its stability is fine, but of late, I get loads of messages saying there's some sort of outage or some sort of issue in the application. I keep getting these notifications from Snowflake, which gives a false impression that something wrong is happening, and it might be underlying in the backend. It doesn't seem that stable.

Its scalability is high. I'd rate it an eight out of ten in terms of scalability.

At this time, we have no plans to increase its usage.

Their support is good.

Prior to Snowflake, it was a completely Greenfield requirement.

It was very straightforward.

It required just two people. One from the Snowflake perspective, and one from my team members' perspective to get the configuration running. That's it.

We haven't yet seen a return on investment because some of the applications are yet to be fruitful and make revenue. We have used Snowflake for the past three years at this point, but we have not yet made great revenue.

It's expensive.

Snowflake is very useful as a data lake and as a data warehouse. Also, it has a lot of features with respect to data science. We are not there yet, but if there are any specific use cases around compute, data distribution, and data sharing, then Snowflake is a tool to be considered.

I'd rate Snowflake a seven out of ten.

The primary use case is for building a database and data link.

I like the ability to work with a managed service on the cloud and that is easy to start with.

From the documentation, the black box is not very descriptive. Snowflake does not reveal how exactly the data is processed or sourced.

I have been using Snowflake for three years now.

The stability is reliable and a standard product.

The scalability is very good and we have around two hundred data sets currently operating.

Technical support is good. It is readily available and they are very responsive.

Positive

The initial setup was straightforward.

You can do the implementation in-house since it is a managed service and only takes a few hours.

The pricing is economical as compared to traditional solutions like Oracle and competitive pricing.

I would rate Snowflake a nine out of ten.

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.

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.

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.

Snowflake is used for very large data, such as in the case where tables might contain 600 to 700 million records.

It's ultra-fast at handling queries, which is what we find very convenient.

The pricing and licensing model is good.

Snowflake has support for stored procedures, but it is not that powerful. They have a lot of limitations. For example, it is really basic and there are limitations on subqueries.

The functions are not very good. Improving this would help to make sure data manipulation much easier. Right now, the inbuilt stored procedures and functions are all Java-based.

I Have been using SnowFlake for about five months.

We have approximately 10 people in the organization who are using Snowflake.

The technical support is very good.

We use Snowflake in conjunction with Matillion, which is another AWS-based ETL tool. It is being used as a bridge between our on-premises data and Snowflake. 

The initial setup is very straightforward. You simply log in and start using it.

When it comes to deployment, you can choose between the AWS and Azure cloud. We chose AWS.

It is easy to create an instance and you can do it yourself if you have an AWS account. Snowflake will give you the connection ID and other relevant details.

The pricing is flexible in that, for example, if I run a query and it is slow then I can increase the processing power while it is still running, and they charge more for the time. The cost is on a per-query basis.

If you're running with a base processor, called a warehouse, the query might cost 1.0 cents. But, if my query is slow and I want to increase the speed, the next level adds a little more cost to that.

On average, with the number of queries that we run, we pay approximately $200 USD per month.

Recently, we have been doing a review of Redshift. However, we finally decided to go with Snowflake.

My advice for anybody who is considering Snowflake is that it is a really good product, especially if you are having issues with Big Data. It is not good for a typical OLTP environment, such as a small table.

I would rate this solution an eight out of ten.