Snowflake Reviews

We are currently using this product for data lake and data warehouse projects. Snowflake creates our repositories and enables the view from other tools like Docker and Power BI to create that data mesh. We use the data to create a process inside the warehouse. We are customers of Snowflake and I'm the senior manager of information technology infrastructure.

Snowflake is user-friendly and reliable in creating the data warehouse and carrying out data modeling. 

I'd like to see the data science functionality improved to a degree that would enable data scientists to work together with the data engineering team. The solution is focused on SQL and some kind of language or free support would be useful and would add some functionality to the machine-learning process. 

The current API is very limited and difficult to configure. It's not easy to create an API and start changing data so some kind of API to expose the data would be good. We use Docker to check the data but if we could get an API that allows other tools to access the data that would be great. 

I've been using this solution for two years. 

The scalability is good. There are around 35 people in the company using Snowflake and six engineers dealing with maintenance. 

The technical support is good. 

Positive

The initial setup was simple and took about a month. The main point is to align the data governance and integration process because you only need to click a button to start. We had a service engineer from Snowflake help with that.

If you use the tool well, you'll see ROI from your investment.

It's important to understand the licensing model because if you're paying for the software, you're not necessarily aware of the use. It's important to monitor how you're using the resources otherwise you can find yourself in a difficult situation. Licensing costs depend on the agreement you have with Snowflake.

I rate this solution nine out of 10. 

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. 

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.

Snowflake is our centralized data warehouse. We bring all of our business critical information to Snowflake. It also powers all of our dashboard's reporting and analytical models.

Snowflake has improved our organization by powering company-wide dashboards that functions use to understand and manage their business. We also have dashboards that go up to our board of directors and our C-suite. Snowflake allows us to have up-to-date, consistent, and useful reporting for the entire company.

I found Snowflake's performance to be its most valuable feature. The product is an incredibly fast and performant data warehouse. We handle a lot of semi-structured data natively with it, which is nice. 

I also appreciate Snowflake's scalability. As the company has grown, as the number of Snowflake users have grown, I have not had any issue scaling.

There is room for improvement in Snowflake's integration with Python. We do a lot of SQL programming in Snowflake, but we go to a different tool to program when we have to in Python. However, I know this is an area that Snowflake's working on.

I have been using Snowflake for a year and a half at my current company. I have an additional six years of previous experience. 

Snowflake is incredibly stable. I have never had an issue with Snowflake outages.

Snowflake is scalable both in terms of the amount of data that you can run through it and the number of users that engage with it. We have five direct users and then, because Snowflake powers all the dashboards, 250 indirect users.

We plan to increase our Snowflake usage in the future. As we send more data through it and build out more sophisticated dashboards and reporting and especially statistical modeling, we will increase our usage.

I have not had a lot of issues with Snowflake, so I haven't had to utilize technical support that much. But when I have had issues, I received a response in a couple days, not the same day. The responses sometimes help solve the issue and sometimes not. The technical support could be better. 

Neutral

I did not previously use a different solution at my current company. 

The initial setup was very straightforward. 

Our employment was done in-house. In fact, I did it myself. 

We have seen a return on investment with Snowflake. 

We spend between $30,000 and $50,000 a year for Snowflake licensing.

I did not evaluate other options. I have been using Snowflake for so long and it has been so good for me to use that didn't need to.

I think Snowflake is fantastic for both storing data and querying your data, but you should always maintain visibility into your costs. They can run up and get out of control if you're not aware of who's using Snowflake and why.

The primary use case is data platforms, specifically data warehousing. It involves restoring and moving data within the platform to prepare it for analysis, routing activities, or serving as the backbone for applications. 

Snowflake also advertises different workstreams, but my customers mostly use it as their core platform to ingest data and serve the onward goals of the wider company.

The most valuable feature of Snowflake is consumption-based costs, which means that you only pay for the storage and compute you use. There's a complete separation of storage and computing, so you don't need to add another server to increase storage or computing. From a costing perspective, it's well-positioned. 

Snowflake's time travel is also incredibly useful, and they have a function called "UNDROP," where you can undo a table drop. Data sharing and replication for Snowflake are strong, and they have a data marketplace with public and private data sets available for sharing. Companies can put their data on the marketplace, and anyone can use it by starting the payment model. The data is provided live straight to you, and it appears as if it were just another database in your own environment.

The main thing I'm excited to see at some point with Snowflake, hopefully - I've not seen anything coming out of it yet - is Git integration into the worksheets and the UI. Sometimes it can be tricky to manage multiple environments if you're purely using Snowflake as your scripting and pipeline environment. This is handleable, so if you use third-party tools like DBT, Matillion, etc., those can help. But if you're looking purely within Snowflake itself, it'd be great to have some form of Git support.

For the future releases, I would love it if they one day decided to implement their own GUI-based transformation tool environment. I know that many competitors like Azure have to Sign Up, and Azure Data Factory can sit in. However, Azure is a very different beast that serves all sorts of different processes, and an argument could be made for whether it's the best to each of those or not. Specifically within Snowflake, I would love it if they could get some form of orchestration built-in for transformation that doesn't have to be controlled directly through code all the time.

I have been using Snowflake for five years. 

It is an incredibly stable solution. It will only go down if your cloud provider itself goes down. So, let's say your Snowflake is hosted in Azure London. If the Azure London data center goes down, I would only see Snowflake going down. If that does happen, Snowflake does have plenty of options for failback replication and rollover backups. 

So we have quite a few customers that, for example, need their data restored in AWS London, and they've got a backup or a replication stored in Azure London. If AWS London goes down, then Azure London one will kick in and become the primary account, and all of the URLs, etcetera, remain the same because they've set up failover URLs and connections for it. At least for the end customer, there's no change. It's only for the architecture and developers behind the scene who then have to double-check things and do all the normal due diligence. But it runs very smoothly

It is a highly scalable solution. There is no limit on storage or computing. They have everything on consumption-based pricing, but you can have what's known as a multi-cluster warehouse. So, warehouses are what you use for the compute.

The multi-cluster warehouses will sit there originally as a single cluster. But then, if there are enough concurrent queries taking place in that warehouse, it can, as it needs, just spin up another one from another one and another one to meet those current needs. And as soon as they can dive down again, it can switch those clusters off again one by one. And you can create as many clusters, warehouses, as many as you need. There is no scaling issue at all. I've seen it most, like, 10,000 queries a second, and it's run very, very smoothly.

The customer service and support team is very useful and strong. They've got support built directly into the Snowflake UI. So wherever you are on the platform, and you see an issue, you can click into the support area and submit your ticket, including direct things like the query ID that you're using or multiple query IDs and all that stuff. 

I find Snowflake to be very responsive, and if you submit a top-level ticket, you can get a response very quickly. The lowest tier of tickets might take 48 hours sometimes, but overall, they are very helpful.

I personally don't see any of the competing cloud platforms coming close right now to what Snowflake offers. An argument could be made with GCP and Datadog are getting closer. Also, a new AWS Redshift is on the horizon, like a whole new AWS Redshift 2.0. But right now, I've not seen anything that comes close. Snowflake, to my understanding, is the only platform that fully separates your storage and computing, essentially. And it's the only platform I've seen with things like time travel. It's got a whole bunch of great features that I don't know if other tools also have, but it supports semi-structured data. It supports automated tasks, alerts, and reporting. And the data sharing is a massive one. GCP now also has its own data-sharing potential, where you can share data with other GCP accounts. I've not used it myself, but to my knowledge, whilst they have the sharing, they don't have anything that even comes close to the Snowflake data marketplace that allows customers to sell or share their data outside the wider world. And it doesn't have anything that comes close to the kind of private equipment where customers might share their own data internally or to their own. And I think there was one more thing. 

Snowflake also have some really good support for Python, Scalar, and Java through what they call Snowpark, which was launched last year. But more recently, this year, it was announced they're really pushing forward with their StreamLINK integration. It will allow customers to host applications on Snowflake and share those applications with other users in a very similar kind of marketplace environment they use for data sharing. I don't think there's anything that any of the other competitors have right now.

The deployment model is delivered as a service. So the most deployment you have to do yourself is by deciding which cloud provider and region you want it to be hosted in. But Snowflake will actually host it themselves, so there's no deployment beyond clicking from a dropdown and clicking okay, and it'll magically appear.

Moreover, it's very easy to maintain because it's delivered entirely as a service. Snowflake takes care of all the patches, upgrades, maintenance, security tweaks, etc.

We have many long-term customers who have been using Snowflake for years, and they wouldn't continue to use it if they weren't seeing a strong return on investment.

There are many options for starting a Snowflake deployment, but I recommend working with a partner who can provide best practices and guidance. It could be through Snowflake directly or another service partner. Working with a partner can save you time and prevent mistakes down the road.

Overall, I would rate the solution a ten out of ten. 

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.

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.

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.