Snowflake Analytics Reviews

We use the Snowflake platform for analytics and for data integration. We are partners with Snowflake. I'm the managing director. 

The solution auto-scales and provides concurrency. You can have different virtual warehouses without them impacting each other. It's flexible and infinitely scalable because it's on the cloud. 

For modeling of data as well as for AI and predictive analytics, they need to improve their integration into different Python and Jupyter notebooks. That is lacking but I understand they're working on it. 

The solution is stable. 

The solution is easily scalable. 

Technical support is good, they'll escalate tickets if need be and they'll get engineers on board if that's what's required. 

The initial setup is straightforward, just click the button. 

The cost depends on the size and on what you're using. I've had customers who spend a million dollars a year and customers that spend $20,000 a year. If you're not using it, it shuts off and you're not paying anything. 

I would recommend starting small and growing into it. Don't overbuy. If you're going to get discounts and you're going to buy a block of credits for the year, make sure you need those blocks because you're not going to peak until the second or third year of implementation. It's easier than a traditional environment and allows for focus on the value that can be provided.

I rate this solution 10 out of 10. 

I like the integrations available in the product. We can send the data to our data warehouse if we want to transform it. I like the cloud solution. It's not necessary to use a physical server.

The UI must be improved. It would be pretty helpful to have some images showing what we are doing and how we use the tool.

I have been using the solution for two years.

I rate the tool’s stability a nine out of ten. We don't have any problem with data orchestration or data transformation. It’s pretty good.

I rate the tool’s scalability a nine out of ten. The tool is dedicated to the data team. Around 20 to 30 people use the product in our organization.

I have used Redshift and other data warehouses from Google. I used them to extract data in Oracle for 18 years while working in a telecom company. I prefer Snowflake over the others.

The initial setup was a little bit hard. It was especially hard to create a connection with the product team. The product team generated the data, and we had to create some tasks before they were sent to Snowflake. It was difficult because everyone was pretty new to the solution and did not have the necessary knowledge then. The setup was not intuitive. By the end, we understood how to deploy it. The product is deployed on the cloud. The initial deployment took one or two weeks. Later, it takes two or three days to change or update things.

We implemented the product in-house.

Using the product is more about our perception and technical skills in data modeling and querying. If we use it well, the tool runs well more than 90% of the time. It’s easy to use the solution because it has everything that we need. It performs well. People who want to use the solution must create a demo account and try using it. We must optimize our SQL queries. It is helpful to understand the volume of our data before writing codes. Overall, I rate the tool a ten out of ten.

Snowflake replaces enterprise data warehouses that have traditionally been on-premise and had to be managed by the enterprises themselves. We are a services company and we create these data platforms for our enterprise customers in a variety of industries including health care, education, travel and tourism. We create and build services around Snowflake and part of my job is to assess its suitability for our enterprise customers. We are partner of Snowflake. 

The solution is completely managed and that's fantastic. Its a true SaaS kind of Data platform. You can create analytical products as a SaaS offering, nothing needs to be installed and no licenses needed. The solution can run on AWS, Azure and on Google Cloud and you can choose the underlying cloud on which Snowflake creates your databases, uses different services, stores your accounts and stores your data. It offers high flexibility. It offers computation completely decoupled from the storage so you pay fees for computation cost only, and storage is very very cheap. For example, within the enterprise data warehouse, if the total compute time is two hours a day but the traditional setup has to be maintained and managed round the clock, and the data also has to be permanently stored, them moving to Snowflake would ensure that the enterprise pay much less for storage, and pay for only 2 hours of computation. Performance-wise also it's a good solution. 

In your data platform, if you have a lot of computations, Snowflake can becomes costlier with. There can be some complexity when designing your warehouses or enterprise data, but that is based on your requirements and not the underlying warehouse that you choose.

I've been using this solution for about 4-5 years.

It's extremely stable because it's backed up, load-balanced and has the elasticity that the underlying cloud (AWS, Azure, GCP) provides. 

The solution is scalable and has the concept of creating virtual resources, so as an example, I can buy 10 gigabytes of data capacity, then decide to process that data every day, Snowflake then takes care of creating multiple databases/storages, and scales by itself. I don't need any calculations of load or throughput worked out beforehand. For most other similar products, such as RedShift or Azure Synapse, you have to work out your average load and peak loads beforehand , and provision the warehouse and other services. In Snowflake, you don't need to do that, it auto-scales up and down.

Customer service has and support are at par with any professional Data Platform service.

Positive

The initial setup is straightforward. You buy an account, and add the number of accounts you need, and that's it. It takes about five minutes. 

The solution can become expensive when you increase your computation. So one has to design the solution very carefully and optimally. Leverage it heavily for Storage, but for compute, make sure the resources (e.g. Virtual Warehouses, Snowpipe, Streams, Tasks etc.) as well as the transformations are used in the most optimum way. For example, during the design time, the technical team has to wisely think if your data marts can be Views or Tables (View consumes compute, but Tables consume Storage), how frequently your data marts need an update, whether you should write lesser but complex queries of more but simpler transformation queries and stored procedures and many other things. But its ease of use, decoupling of Compute from Storage, ability to share data, and highly managed behavior make it worth the money.

I highly recommend Snowflake wherever possible. 

I rate this solution 9 out of 10. 

We wanted a solution which is on cloud and gives us data warehousing and analytics capabilities, so these are our use cases for Snowflake Analytics.

Snowflake Analytics improved our organization because it was capable of doing what we needed. They are also coming up with more characteristics or more features, but at this point in time, what's currently available in the solution is very convenient for us to use. We've incorporated the features of Snowflake Analytics according to our business needs.

What we found most valuable in Snowflake Analytics are its attributes that are very convenient for business use such as data sharing, cloning, time travel, and fail-safe. It's a good product all in all.

A room for improvement in Snowflake Analytics is Spark, particularly its connector for Spark.

An additional feature I'd like to see in the next release of the solution is built-in analytics.

I've been using Snowflake Analytics for more than two years, and I've used it within the last twelve months.

Snowflake Analytics is a stable solution.

Snowflake Analytics is a completely scalable solution.

The technical support for Snowflake Analytics is responsive, and on a scale of one to five, I'm rating support a four.

The initial setup for Snowflake Analytics was easy. The deployment time for the solution was, on average, five to six hours, and it was dependent on the user history created for a particular sprint.

As of now, I have not seen ROI from Snowflake Analytics.

I'm unable to give information about the licensing fees for Snowflake Analytics because it's the infrastructure team who takes care of licensing completely.

I have experience with Snowflake Analytics, and I'm using its latest version. The solution is deployed on the public cloud, on AWS.

There are two users of the solution within the company, and we have two people, particularly IT analysts, in charge of the deployment and maintenance of Snowflake Analytics. There's a plan to increase usage of the solution within the company.

My advice to others looking into implementing Snowflake Analytics is that if you are looking for a stable solution with good features for upcoming business problems, you can go with cloud data warehouse technology such as this solution.

I would rate Snowflake Analytics eight out of ten. I'm not giving it a perfect score because there is always room for improvement, for example, built-in analytics and its Spark connector.

My company is a partner of the vendor and implements Snowflake Analytics.

The solution is a flexible data warehouse. It can be used for computing and storage. There's also the potential for automation. With Snowflake, you can use the same copy in multiple places.

Once your data is on Snowflake, you can have that data differential to reportings. You can start using the analytics on top of it as well.

The data integration is great. We don't have to do data pipeline creation or time travel testing. 

The storage is good.

It's got good optimization.

We really like the engineering and the data within Snowflake.

The performance has been good.

We like how we can have one copy that can be used in multiple places. 

We haven't seen any areas that are lacking. I can't recall coming across missing features. Over the last two to three years, we haven't had issues. 

I've used the solution for almost three years now.

The solution is stable. A lot of it comes pre-configured and we haven't had any issues with it. There are no bugs or glitches and it doesn't crash or freeze.

With Snowflake, you are using the cloud, storing data in a cloud. It's scalable for that reason. It's not a problem if you need to have more data or more space.

Typically, the client will have their own support team. We don't really deal with the support side of things. 

My understanding is that their support is pretty good and clients are happy with their level of service. They work hard to resolve issues. 

Positive

The deployments vary. We first need to understand what the deployment is, and how much data will be pulled. When it comes to implementation, sometimes clients do some revisions and that must be taken into account as well. 

You need some expertise. Setting up Snowflake, the installation, configuration, and everything, are all separate skills altogether. 

That said, it's not overly difficult. Most of it the things you're doing are automatic value configuring for the grid function.

We are able to handle the initial setup for clients. We collaborate with Snowflake.

We haven't witnessed any ROI, however, it's not really a goal of the solution. 

The cost of the solution depends on how much you are using it, and therefore, the pricing can vary from company to company.

We are partners with Snowflake. 

In the last four or five years, Snowflake has actually blown up. Before that, it was quite low in terms of visibility and potential. We have now done multiple engagements on Snowflake.

Right now the snowflake is adding the multiple clients we using all editions.

We're using a variety of clouds, including AWS and Azure. 

I'd rate the solution nine out of ten. While we've done many complex implementations, Snowflake always has a way of simplifying things. 

One advantage is that installation is unnecessary since it's cloud-based. You subscribe to a Snowflake instance, configure it, and start using it. It's very user-friendly and allows you to scale up or down based on usage.

I don't see many drawbacks with Snowflake Analytics, but it's not as mature as other tools. It is evolving and needs to integrate various features, like data loading and analytics, better. These components are not fully connected, so the tool should become a more integrated application.

The solution is costlier than Azure or other tools like Pentaho, which are cheaper but require more effort in ETL or ELT development and integrating all the tools.

Snowflake Analytics integrates well with the data, keeping everything within the same network and premises, eliminating network latency, and ensuring fast performance. Scalability is a strong point, as the compute and storage layers are separate, allowing independent scaling. This elasticity means that as more users or developers work on it, Snowflake can handle any load by leveraging CPU and GPU capacity.

I rate the overall solution an eight out of ten. 

One of the valuable features is the solution’s time travel capability. The loading process exhibits characteristics of low coding for similar loads. Unlike before, where extensive scripting was necessary, Snowflake Analytics simplifies tasks such as file exposure through SQL, a familiar and flexible language for all. Even common commands like the copy command become more straightforward, making coding in this solution more accessible and efficient.

The solution’s interface is good but it could be improved.

I have worked with the solution for almost three years.

The solution is highly stable.

The solution is highly scalable. We cater to enterprise businesses. I rate it a perfect ten.

The initial setup is straightforward, and the deployment process is quick and efficient.

The solution's pricing is affordable.

I recommend the solution. Overall, I rate it a perfect ten.

We use Snowflake Analytics as the main data source for a project.

The most valuable feature of Snowflake Analytics is the ability to control and manage the cost.

The solution’s scalability could be improved.

I have been using Snowflake Analytics for about two and a half years.

The solution's stability is pretty good. I rate Snowflake Analytics a nine out of ten for stability.

Around 1,000 users use the solution in our organization.

I rate Snowflake Analytics a six out of ten for scalability because we faced some issues on big projects.

The solution's technical support team responds on time, but some complicated issues take time to be resolved.

Snowflake Analytics is not an expensive solution, and its pricing is average.

Overall, I rate Snowflake Analytics an eight out of ten.