Snowflake Reviews

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

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

The solution's stability needs improvement.

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

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

I rate the solution's scalability as a nine.

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

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

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.

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. 

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.