Snowflake Reviews

I have used it in my previous company. It was just a SQL server data warehouse using reporting tools on top of it. It was an on-premise SQL server environment, and it was a typical data warehouse use case, but we wanted to do things faster and more cost-effectively. 

We used it to modernize our data warehouse. We didn't want to invest more in on-premise servers, and we were looking for a way to quickly get more data joined together. 

It had definitely improved the way our organization functioned at the time.

The overall ecosystem was easy to manage. Given that we weren't a very highly technical group, it was preferable to other things we looked at because it could do all of the cloud tunings. It can tune your data warehouse to an appropriate size for controlled billing, resume and sleep functions, and all such things. It was much more simple than doing native Azure or AWS development. 

It was stable, and their support was also perfect. It was also very easy to deploy. It was one of those rare times where they did exactly what they said they could do.

Their strategy is just to leverage what you've got and put Snowflake in the middle. It does work well with other tools. You have to buy a separate reporting tool and a separate data loading tool, whereas, in some platforms, these tools are baked in. In the long-term, they'll need to add more direct partnerships to the ecosystem so that it's not like adding on tools around Snowflake to make it work. They can also consider including Snowflake native reporting tools versus partnering with other reporting tools. It would kind of change where they sit in the market.

I have been using this solution for about three years.

We didn't run into anything. We had outages for a couple of seconds, but they were related to Amazon or AWS. They weren't related to Snowflake.

We scaled it a little bit. We didn't have a lot of data to scale, as a lot of companies do. We only had a couple of terabytes of data, which is insignificant for a cloud platform. 

The development team had three or four people getting data in. Then report people were also using the platform, but they didn't really have to know that it was Snowflake because they were going at it through a reporting tool. There were probably 30 or 40 people writing queries against our reporting tools, which were, in turn, using Snowflake.

They were really good. They were very responsive. There were never any issues with them. I would give them a ten out of ten.

I've used a lot of different data warehousing solutions at different companies.

It was easy as pie. In a couple of hours, it was up and running, and we were loading the data in. We had a fairly senior developer for that. He knew SQL server and queries very well. If you're used to developing in any type of SQL environment, you can jump in and use Snowflake really quickly.

It is per credit. It has a use-it-as-you-go model. We bought a chunk of 20,000 credits, and they were lasting us for at least a year. We didn't have the scale of data like a much larger company to consume more credits. For us, it was very inexpensive.

Their strategy is just to leverage what you've got and put Snowflake in the middle. It doesn't make it expensive because most of the organizations already have reporting tools. Now, if you were starting from scratch, it might be cheaper to go a different way.

If time to value is your primary goal, then I would recommend going for Snowflake over one of the other cloud providers.

I would rate Snowflake a ten out of ten. It is one of the few products in which everything demos well. It actually did everything they showed in the demos. We really couldn't find any gotchas in it. It kind of delivered as promised.

We use this solution for business intelligence. We have three persons in the team for developing the end product.

Snowflake is a database, and it is very good and useful. The most interesting part is that memory management is very good in Snowflake. For a business intelligence project, SQL Server is taking a lot of time for reporting services. There are a lot of calculations, and the reporting time is shown as two minutes, whereas Snowflake is taking just two seconds for the same reporting services.

For the Snowflake database, there should be some third-party features for the ETL. It would also be good to be able to use some kind of controls to get the data either from another database or a flat file.

Its price should be improved. It should be cheaper than Microsoft.

I have been using this solution for eight to ten months.

It is stable.

It is scalable.

Their technical support is good. I always get a response from them when I send an email to their support team.

It is very easy to install. After the installation, you just have to input some information into the Snowflake database. It is very easy.

Its price should be improved. It should be cheaper than Microsoft.

I would recommend this solution. I would rate Snowflake an eight out of ten.

We primarily use the solution for the data warehouse.

The solution offers everything you'd find on Azure or AWS. It has a lot of industry-standard features and capabilities.

The product has excellent autoscaling. We can actually compute and scale-out at the same time without having to depend on other tools. You can do it on the fly, or within queries, etc.

The Visual Copy Cloning is definitely one feature that everyone looks forward to due to the fact that it gives you regular backups. 

The solution offers a very good time travel function that allows you to travel back in time to before your systems we corrupted. You can go back into your history and grab the last backup before corruption so that you regain almost everything you need. It gives you 90 days to fetch the data back if you need to. It's better than Azure options.

We've spoken with Snowflake about the fact that there are a few bare minimum requirements now these days for any data cloud, data lake, or platform. They've lacked a bit here, however, they're adopting some new measures that will be available in the next release, so that is sorted.

Snowflake is partners with only AWS as a cloud platform. However, in India, Microsoft has got a big subscription. The product needs to be able to adapt to Azure a bit more in order to meet the local market demands. 

It's difficult to know how to size everything correctly.

They should incorporate at least a basic ETL framework.

It's early days, however, I would put the solution at a seven out of ten. It needs a bit more time to mature. If I were to look at it strictly from a warehousing perspective, I'd rate it at an eight out of ten.

I've been using the solution for about ten months. I started using it originally when we started our partnership with the organization.

The one thing that seems to be unclear for Snowflake customers is the cluster sizing. No one seems ot know how to compute that.

For example, if I'm running a warehouse that is extra small, as per my query performance, if I see like if this query will run perfectly on the machine I will have. However, I don't know which machine to go for. There's no direct comparison between an extra small, or a small, or a medium warehouse. I never get to know, unless I run the case query on different sizes, which to go for. It's hard to say "Buy only this and go for that particular size". Sizing seems to be a bit of trial and error. If they had some sort of benchmarking around their cluster size, that would be helpful.

The initial setup is pretty straightforward. We didn't have any issues with implementation. It's not too complex.

The pricing of the solution is fine. The storage is pretty cheap. They also offer a lot of discounts. The cost shouldn't really be a problem. 

That said, the agreement should be more of a subscription basis instead of asking for a commitment. For example, Microsoft tells your the price and allows you to subscribe to that, whereas, Snowflake wants you to commit to a certain amount of time before they really give you firm pricing. 

We're partners with Snowflake. We've been partners for just under a year at this point.

I'd definitely recommend the product. It's worked quite well for us. 

A new customer needs to understand, however, that they need a roadmap of at least five years when they are deciding on their data warehouse. They should compare costs and sizing to make sure they are getting the solution that makes sense for their current and future needs. 

The solution integrates well with other applications, and if you need it to integrate with existing applications, you still should check to make sure it's possible.

I wouldn't necessarily recommend Azure over Snowflake, as they aren't really a good comparison. Snowflake is more focused on data repositories and data warehouses. AWS does give you many options, however.

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.

We work with multiple customers who were asking for this and other similar solutions. We've since had several team members certified in Snowflake and we have a certified team working with that solution and keeping up to date with developments. I'm the general manager of the company and we are implementers. 

Snowflake has its own features in comparison to other similar solutions like Exadata. This gives it huge competitive power. It has a very good interface tool with its own benefits and features which are really useful for our needs from a computation and storage perspective. I think this solution provides the best potential of any data warehousing product where they choose to use Snowflake instead of Oracle or DBII. The product can be leveraged with respect to better performance, auto tuning, competition and performance. From an architectural perspective, the solution has all the ingredients it requires. 

We've come to realize that for many customers, pricing of this solution is an issue. Maintaining Snowflake clusters is challenging and cost intensive. Reporting could also be improved. Any data that moves out of Snowflake is being cached. If I have 400 to 500 end users, with 100 or 200 reports on a daily basis, all the reports will be cached. It's a matter of ensuring that costs can be optimized. The combination of Red Warescape plus Snowflake is a combination from the design and development perspective. But the combination from the reporting perspective to micro strategy on top of Snowflake could be a better feature, so there's a combination that has to be considered.

I've been using this solution for about 10 months. 

Our customers tell us that it is a stable solution. 

We're working in 32 countries with enterprise size customers. We're still waiting to see what happens with that level of scalability and how the solution performs. If this product can be further fine-tuned or optimized in such a way that it becomes a very good fit for the Azure platform, that would be great. 

They provide very good documentation on implementation design and development perspectives. 

I think the initial setup is straightforward. Anyone who has worked on these types of solutions will pick it up quickly.

It really depends on the nature of the implementation. If it's a small or medium sized company, we focus more on the pricing. If that can be brought down, I think Snowflake has a high potential that it can meet and can create a big name for itself in the big data cloud implementation platform. It has all the features. It already has all the complementary features to deal with the challenges. Those are built in and taken care of. It could be on Google cloud, or it could be on Azure or it could be on Amazon.

I'll rate this solution a nine out of 10. 

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.

The primary use case for Snowflake is in our data warehouse project. We have a private DW and whoever has the credentials can access it. I am a data integration developer and we are using ETL tools to extract the data from different source systems and then load it in the data warehouse.

Snowflake is the latest technology. It has great flexibility whenever we are loading data and performs ELT (extract, load, transform) techniques instead of ETL.

This solution automatically performs micro-partitioning when the data is loaded. This creates a dynamic partition and based on the cluster, the performance is fast and really impressive.

Snowflake is using MPP, massively parallel processing techniques, which is a great feature. It saves developers time and allows us to focus more on client requirements.

It is difficult in some cases to perform ETL and this is something that should be included. As it is now, I use Informatica PowerCenter to load data from on-premises to the Snowflake cloud-based data warehouse. If this could be done by Snowflake directly, without an external integration tool, then it would become a full package. It would be awesome.

They do have a native connector to connect with integration tools for loading data, but it would be much better to have the functionality built-in. We would like to be able to just write an SQL query and do our work.

I have been working with Snowflake for six months.

We have not had any major issues with stability.

Snowflake does not require manual scaling because it does it for you. Developers just need to load the data and process the query. That's it. The developer's job is not to spend time improving performance, as it was with an on-premises solution. We had to do the partitioning, collect the stats, and everything else. In the case of this cloud-based solution, it doesn't require as much work. Instead, we can focus on the queries.

We are planning to increase our usage of Snowflake.

I have been in contact with technical support many times and it was awesome. I got great support. Whenever I needed anything they were ready to help me out, which was nice.

I have experience with Informatica PowerCenter and Oracle. PowerCenter uses ETL techniques instead of ELT. Oracle does not automatically perform micro-partitioning. Instead, you have to partition manually and it is a static partition.

Prior to Snowflake, I was using an on-premises data warehouse. Snowflake is the first experience I have had with a cloud-based data warehouse. It is an awesome tool.

There is no need to install this software, which is the best part. It doesn't require any maintenance, and although DBA support is required, it is much less compared to an on-premises solution. This type of cloud-based solution has no requirement for software, hardware, or maintenance because everything is managed by Snowflake's system.

The only assistance I had during the setup was from the integration tool, Informatica PowerCenter. This was used to export our on-premises data from Oracle and import it to Snowflake on the cloud.

You pay based on the data that you are storing in the data warehouse and there are no maintenance costs.

This is an awesome tool, but there is room for improvement in terms of integration. Also, in terms of management, nothing is perfect and everything can be improved.

I would rate this solution an eight out of ten.

We use the solution for data storage and integration purposes.

The solution's most valuable feature is path application.

They should improve the performance of the solution's transaction application.

It is a stable solution.

We have 20-30 solution users in our organization.

The solution's customer service is good.

The solution's initial setup was very straightforward.

The price for the solution's license depends on the use cases.

I recommend the solution to others and rate it as a nine. It efficiently processes the data and gets reports as well.