Snowflake Reviews

We use this solution to ingest e-commerce advertising and web analytics data and completing an analysis. There are 60 people using this solution in our business. 

We are working with a TV advertising agency and they were able to set up a Snowflake data share to share ad spend with us and it was very quick to integrate.

The most valuable feature has been the Snowflake data sharing and dynamic data masking.

The cost efficiency and monitoring of this solution could be improved. It's easy to spend a lot on Snowflake and it does offer monitoring tools but they're pretty basic.

I have been using this solution for three years. 

This is a stable solution. 

This is a scalable solution. 

I would rate the technical support for this solution a four out of five. 

We previously used Amazon Redshift.

 The initial setup was straightforward.

We did have a consultant help us.

We do see a return on investment.

Pricing is based on usage. It is the most expensive of our data tools.

I would advise others to check costs when implementing any changes, such as new BI tools or a new data source. Set up different warehouses for your different tools so that you can track cost.

I would rate this solution a nine out of ten.

We use this product basically for developing an IoT (Internet of Things). Currently, we are sending data from our S3 (Simple Storage Service) storage. In the future, we are planning to directly stream data to Snowflake.

In terms of features, we have not yet explored the product completely. So we are still in the proof of concept phase. As of now, the product meets our preliminary requirements. The snapshot feature is good and the rollback feature is good. That is why we have the product and these are the key things we need.

The recovery process is very simple and very user-friendly as well. The constraint files could be improved. But the most important things are there. Also, the interface is good to work with and user-friendly.

If I had to say what needs improvement, in my experience is that the availability is a problem. Availability should be high and has to be enhanced.

I still have not explored all of the existing features. Because I have not been deeply involved with using the program it is hard to say what else is missing or what I would need.

We have just explored the product for a few months.

The stability of Snowflake is very good.

Scalability is very good and very simple.

Within the company, we currently have a total of fewer than 50 people using the product. Their general roles vary from data analyst to data scientist, to IT professionals, and maybe one or two of the upper managers.

I tried using technical support once and they were very helpful. But after that, I have not had any reason to explore the support services.

The initial setup was simple.

The implementation was done by the vendor.

Before choosing to work with Snowflake we looked at virtual solutions and we looked at Redshift, we looked at Qubole and a couple of other cloud options. Earlier when we did a mining site, I was working with Alteryx, so I was already familiar with that product and its capabilities to use for comparison. We decided to go with Snowflake because it seemed mature and had what we wanted.

My advice to someone who is looking at Snowflake is that if they are looking at analytics tools in addition to warehousing and certain advantages of cloud computing, then I would suggest Snowflake. But if they are just looking for the warehousing part where you will later just use another solution on top of it, then I would not suggest Snowflake.

On a scale from one to ten where one is the worst and ten is the best, I would rate Snowflake as an eight or nine. Let's say 8.5.

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.

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 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.

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.

Basically, if at all, we wanted to have an interface for data warehouses on the cloud which worked on Azure or AWS. Snowflake, provides a more intuitive, rapid user interface where people can connect and maintain warehouses and share data among the people in the companies easily. Its pricing model and the model have made maintaining virtual warehouses simpler.

I appreciate the Snowflake marketplace, where you can drop data and allow other people throughout the world to access it. You can go to the Snowflake marketplace and connect to some data. If somebody else publishes, for example, COVID-19 data or weather data, you can sign up for new data sets and bring them into your warehouse, which I found very interesting.

You can connect to different cloud sources, including Azure and AWS. 

You can report out, and all the cloud technologies have connected to Snowflake, allowing you to move the data or get the data into Snowflake. 

The initial setup was pretty simple. 

It scales really well. 

The solution is stable. 

The solution is reasonably priced. 

I don't know about GCP, if they have connected for GCP. If they don't, they should allow for it.

Overall, they're doing great. I don't have any specific complaints or improvements that need to happen.

I've used the solution for a couple of years now. 

The solution is quite stable since everything is in the cloud, and the data these days has become cheap with storage and everything in the cloud. Through clusters and warehouses, sizes can be increased or decreased based on usage, and they can be turned on and turned off. Sustainability-wise, I think it's a pretty good solution.

It is scalable. The warehouses or auto-scaling features in the warehouses are great. You can go from small to medium to large all the way up to extra large, and there are different auto-scaling tasks that can happen. You can turn it on and turn it off based on the usage or auto-turn it on and turn it off. That's a pretty nice feature to have and we find it both sustainable and scalable for sure.

I work for clients, so last time when I worked for a client, there was a group of 100 people who were actually signed up to use Snowflake. 

I've never dealt with technical support. We did have people from Snowflake working with us directly, and we never ran into any issues that needed troubleshooting. The personnel from Snowflake, of course, would resolve whatever came up. 

I come from an Azure background as well, so Microsoft also comes with Azure Synapse, where it's a similar functionality as Snowflake, where it's warehousing on the cloud. Azure Synapse is also good. I'm unaware of AWS or GCP, and I heard that Google Cloud Platform also has Big Query and big data capabilities, which are tough competitors for Snowflake and other cloud warehousing tools.

The implementation process was pretty straightforward. I didn't set it up, though. I used an already set up version. I just had to connect. I had to push data from Azure to Snowflake, create tables there, and have data loaded into those tables, and that's it. I wasn't doing anything else, so I didn't work on the infrastructure of Snowflake.

You would need a group of two or three people to maintain the product.

I work for a consulting firm, so I don't work for the client, so I really don't know what the company used for deployment.

Licensing was based on the warehouse. I don't recall it being very expensive. 

I'm a consultant and end-user.

I'm not currently using the solution right now and do not recall the last version I was on. 

Now, I'm working for a different client on a different platform altogether. My company, as such, doesn't use Snowflake since we are in consulting. We have expertise in something, and then we help the clients deliver that solution on the technology.

Potential new users should just definitely give it a shot. They should start off with a POC, proof of concept, for the data that they have, and then, if everything works well and they can migrate in a cost-effective way. 

I would recommend Snowflake to start off with since it's just picking up over the last couple of years. If I have to recommend anything, however, it would be more Microsoft tools I would recommend since that all comes as a package. You can do Synapse and Azure Data Factory, which is  for ETL. You can also do Azure Data Lake Storage. There are different things that you can do when you buy something in a package like that. That said, I definitely recommend Snowflake if someone wants to give it a shot.

I'd rate the solution eight out of ten.