Snowflake Reviews

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.

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.

Our company uses the solution for building a data platform, data warehouse, and data transformation.

The product is somewhat used for data analytics, but it is mostly for data engineering.

The tool is good for handling large datasets, and since the tool is fully managed by Snowflake, you can scale up the compute part.

I don't think that the AI tools in Snowflake are good. AI tools in Snowflake can be improved. Even if the AI tools in Snowflake are good, I feel that it would be expensive. The cost of the AI part does not justify what you get from the product.

The price of the product can be lowered.

I think Snowflake should integrate with some tools like ChatGPT.

I have been using Snowflake for a year.

The product is scalable and can be considered a good fit for small and medium businesses.

I haven't directly contacted the technical support team of the product.

I have used Azure Databricks and Azure Data Factory. My company decided to use Snowflake since we wanted to be able to get up and running fast without much configuration-related mess. Snowflake doesn't give you the options with the configuration part since, by default, it is available out of the box. In terms of machine learning, Azure Databricks has the upper hand over other products.

The product's deployment phase was quite okay.

The solution can be deployed in a few days or up to a week.

The product's price range falls between average to a bit expensive range. I think the tool is worth the money if you use it properly. It is difficult for me to speak about the number of users who use the product. My company pays around a couple of thousand dollars a month to 10,000 dollars or more.

I think the main benefit is that with the tool, you can easily get things going without problems since you don't need to configure all the parameters manually. If you buy the tool for a bigger computing purpose, the engineer can pay more attention to the tool, and I guess after that, you can do more with the solution. I would ask others not to think about the data warehouses, as Snowflake takes care of such areas.

The benefits from the use of the product can be realized in around 40 minutes. It is a good technology for getting up and running quickly.

Snowflake is integrated with Azure Data Platform and other ETL tools in our company's ecosystem.

The integration capabilities of the product are good and you get what you pay for when it comes to Snowflake.

I rate the tool a seven to eight 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. 

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. 

Our primary use case for Snowflake is inputting data generated by AWS.

This solution has helped our organization by being easy to maintain and having good technical support.

The features I have found most valuable are the options to connect with extendable sources in three buckets in which we can also create stages.

I think that Snowflake could improve its user interface. The current one is not interactive.

I have been using this solution for about one year.

I would rate the stability of this solution a nine, on a scale from one to 10, with one being the worst and 10 being the best.

I would rate the scalability of this solution a 10, on a scale from one to 10, with one being the worst and 10 being the best. There are around five developers in our company and 500 end users for this solution.

We previously worked in AWS.

I would rate the initial setup process an eight, on a scale from one to 10, with one being the worst and 10 being the best.

I would advise other people trying to use this solution to build a skill balance as it's quite difficult to work in Snowflake.

I would rate this solution as a whole a nine, on a scale from one to 10, with one being the worst and 10 being the best.

Our current plan and use case for this solution is to migrate the data from on-premises to the cloud. We are currently using on-prem monitor data and providing it on the cloud. We are using Snowflake so that once the data is in there, we are trying to create shares over it so that external systems can't consume it.

The features I found most valuable with this solution are sharing options and built-in time zone conversion.

I see room for improvement when it comes to credit performance. The other thing I'd like to be improved is the warehouse facility. 

In the next release, I'd like to see easier connectivity to the on-premises tools.

I have been using this solution for about three years.

My impression from using this product for the last three years is that it is quite stable.

My impression is that this is a scalable solution. There are around 200 users of this solution at our company, including three administrators.

The initial setup process was not that complex and it took around six months.

The implementation was done by an in-house team.

My impression is that the pricing of this solution is reasonable.

I would rate this solution a seven, on a scale from one to 10, with one being the worst and 10 being the best.

I mostly build or design data warehouse analytics solutions using Snowflake.

The productivity across the teams that use Snowflake I believe is higher than it would be without the solution.

Snowflake has three great features: Snowpiping is proving to be very valuable, Time Travel is excellent, and Snowpipes are another great functionality the solution has made available.

Snowflake needs transparency over costs and pricing.

I have been using the solution for three years.

I give the stability an eight out of ten. We rarely have issues.

I give the scalability an eight out of ten.

I have used many on-premise solutions in the past and also Azure Synapse Analytics.

The initial setup is straightforward. I give the setup an eight out of ten.

A basic implementation is quick and we only have to set up Snowflake and the cloud service. We need one engineer and one designer for the implementation.

Depending on the complexity of the implementation, we may need to use a third party or help from the vendor.

Part of the problem with the pricing is that it is very difficult for businesses to get an idea of how expensive it might be until they actually start using Snowflake. Until they start pushing large amounts of data through, we will not really know. I believe that it is very difficult for businesses to make a commitment.

I give the solution an eight out of ten.

My advice is to start Snowflake and not spend too much time thinking about how we could use the solution or what it could be used for. The key is just getting started.

In our organization, data is often spread out over multiple on-premise and cloud-based platforms. Snowflake is an agnostic platform, meaning it can be used regardless of which cloud provider we use and can serve as a single source for all of our data. Our use case then is to ensure that all data is located in one place, utilizing Snowflake as the platform.

With Snowflake, productivity can be increased. Snowflake is faster than on-premise systems and allows for variable compute power based on need. We are currently experimenting with ways to reduce processing time from eight hours to six hours or even less.

The vendor claims that the provision of warming sensors quickly enables warmth to compute nodes, which is their Unique Selling Point. From my experience, this has proven to be true.

For the past year and a half, I have experimented with different proof of concept. I have wanted to use Snowflake, however, I have not been able to do so. Microsoft Azure is superior to Snowflake in terms of its machine learning and artificial intelligence capabilities. Snowflake has its own unique products, but Azure surpasses it in those areas. Snowflake can improve its machine learning and AI capabilities.

I have been using the solution for one and a half years.

I found that Snowflake is highly stable, which is a reflection of the quality of its network.

I have gone to the extremes from a scalability perspective and I give Snowflake's scalability an eight out of ten.

As a premium customer for all these solutions, we have received excellent support overall with no issues encountered thus far. However, it is possible that some users of the free version may be experiencing some issues. I cannot confirm this, but from my experience, there have been no difficulties.

I give the initial setup a seven out of ten for ease and time required.

We are leveraging Snowflake, a cloud-based platform, both independently and in collaboration with the vendor. Our objectives for utilizing Snowflake are distinct from those of the vendor.

Comparing Snowflake to on-prem options such as Oracle or SAP, it seemed more cost-effective. With Vantage, a one-time purchase allows for use as many times and to a large capacity, whereas Snowflake, Azure, and similar services become increasingly expensive as the scale increases. Determining the best point of cost-effectiveness requires further study.

I have tested all the different alternatives to Snowflake as well. It is hard to determine which one is the most suitable, as each has its own advantages and disadvantages.

I give the solution an eight out of ten.

Deciding between Azure Synapse and Snowflake can be difficult, as the best choice depends on one's own use case. Ultimately, it comes down to the available connectors; the product with more connectors is likely the better option. When making a decision, one should consider which other sources they would want to get data from and where they want to send data to. This can help inform their product selection.

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.

I am using Snowflake for all our apps and data warehousing requirements.

The most valuable feature of Snowflake is it's an all-in-one data warehousing solution. 

Snowflake could improve migration. It should be made easier. It would be beneficial if it could offer some OLTP features. One of our customers was using Oracle for both data warehousing and OLTP workloads, and they were able to migrate their data warehousing workloads to Snowflake without major issues. However, for some of their OLTP requirements, such as needing a response time of fewer than 10 milliseconds for certain queries, Snowflake is currently unable to provide that.

It would be beneficial to see more integration and reporting tools embedded within the platform, similar to what Microsoft offers with its data warehouse and database solutions. Oracle, on the other hand, does not have such features. While Snowflake has a lot of options available on its marketplace, it would be helpful if it could provide more optimal options for users who are migrating from other environments. It would be great if they could follow the same path as Microsoft in this regard.

I have been using Snowflake for approximately one year.

Snowflake is stable.

We have two clients using this solution.

The solution is highly scalable.

We don't have direct support for Snowflake as we support our clients. If any support is required, our clients connect with Snowflake's support team and get the necessary assistance. They own the support account.

The initial setup of Snowflake is easy. We only need to create a login, there is no conventional setup.

When it comes to migrating from a previous platform to Snowflake, it largely depends on the size of the data warehouse, the number of integrations, the existing data pipelines, and the type of data sources. The complexity and size of the current deployment will determine how difficult the migration process will be.

The ROI appears good on paper, particularly in terms of cost reduction in operations. However, as companies have only been using Snowflake for a year and it's hard to say for sure. It looks promising for now, but it will take a year or so to see if it holds up in practice.

Snowflake is a cloud-based solution that uses a pay-as-you-go model. The storage and processing are separated, and you are mainly charged for the processing power you use. Additionally, there is a charge for storage, but the primary cost comes from the processing. You can choose different sizes of processing units, also known as warehouses, for your specific workload or requirements. You pay for the per-second utilization of those computing resources.

Snowflake is cost-effective. However, the cost can depend on how it's being used and how efficiently the code is written. If engineers don't write efficient code and usage is billed based on processing, it can become costly. If they write optimal code and choose the best solution, it can reduce costs in comparison to other options, such as Oracle.

I would recommend this solution to others.

I rate Snowflake an eight out of ten.