Snowflake Analytics Reviews

We use it for our full application operational analytics, including building, storing, and analyzing the data. It provides us with detailed insight, making it easy to extract needed reports. Everything related to business intelligence, whether it's reporting or analytical modules, is stored on the Snowflake Analytics platform.

It's an intuitive platform that allows organizations to rapidly adapt, providing the ability to quickly analyze and make data-driven decisions. It ensures the optimization of the application development while maintaining the user-friendly nature of its UI.

Machine learning should be improved. Some of the solutions, such as Databricks, offer an option to directly write and integrate Python code on the spot, but Snowflake doesn't have that feature yet. Adding it would be useful, as it would facilitate building models.

I have been working with Snowflake Analytics for a year.

It is a stable platform.

It offers good scalability.

I am highly satisfied with their level of customer service and support. I would rate it nine out of ten.

The initial setup was done seamlessly.

There was no requirement for installation. They provided us with a link, giving us access to the cloud.

It is an expensive solution, but the kind of usability and flexibility it proactively provides for the organizations justify the price.

Snowflake Analytics is a really good choice for organizations that are looking at a cloud analytics platform for reporting, data modeling, and advanced analytics without machine learning requirements.

Using Snowflake, I can say it is built as a robust solution. Also, its analytical functioning is really quick.

Using Snowflake to load data from different sources is a valuable feature of the solution.

The solution needs to consider including some updates in the future. There is a need to add some new features to the solution to facilitate my work with Snowflake.

I have been using Snowflake Analytics for a year and two months. I'm using it because I'm a data engineer, and so I am a customer of Snowflake.

In my experience, I didn't face any crashes or anything related to data. So I think it's stable.

It's a scalable solution because you can analyze a huge amount of data in the solution. In my company, around ten developers are using the solution.

The initial setup is easy because it is a cloud solution. So you don't need to install anything. You can just connect to your account and write SQL queries or write the procedures. So you can manipulate it on the website directly, and also it's user-friendly.

The solution has some gold and premium plans, which I read in its documentation.

I would tell others to use the solution if it is available for them on the cloud since I think it's very easy to manipulate data and work with it. Also, it is not very difficult because it is based on SQL queries, JavaScript, and Python.

Overall, I rate the solution an eight out of ten.

We use the product to generate insights. 

I am impressed with the product's data-sharing feature. 

The tool should support EIM use cases. I guess the product is already working on it. I look forward to seeing inbuilt AI generative tools in the solution's future releases. The tool's price can be a little lower. The solution's on-premises support is also very limited. We have to rely on other support services to deploy it on-premises. 

I have been working with the solution for four years. 

I would rate the product's stability a nine out of ten since it is stable and reliable. 

I would rate the tool's scalability a nine out of ten. My company has more than 1000 users for the tool. 

The solution's support responds fast. 

Positive

I would rate the solution's setup a nine out of ten. Being a SaaS product, the setup is straightforward. The solution's setup becomes complex only when you need to create a specific cloud platform which is virtual or public. If you have a CI/CD pipeline ready, then deployment can be automated. The tool's deployment doesn't take more than a day to complete. 

The solution's price is high and I would rate it an eight out of ten. 

I would rate it an eight out of ten. The solution is very easy to use. The tool is a SaaS product. You can leverage your overall data analytics strategy with the solution. It has a lot of features and you shouldn't consider it for data storage alone. In the future, we will be able to leverage the solution of ML-oriented used cases as well. 

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. 

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.

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.

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. 

We use this solution to move on-prem data to a cloud data warehouse where we have a requirement for more computation storage or when we need a plugin to work with specific technologies like ML, AI and Data Science. 

The advanced features like time travel, zero copy cloning and scalability have been most useful. Snowflake requires zero maintenance for Data Warehousing on the cloud system. It is more secure compared to any other data platforms that we have used. The tri secret key is the feature that gives a lot of confidence to customers. 

Moving data from legacy systems to Snowflake is not that easy. There are some cases where processors are not actually compatible with Snowflake. If Snowflake could offer compatible versions of other legacy system objects, that would be more convenient for anyone to move to Snowflake. 

When comparing MySQL with Snowflake, MySQL is faster in executing the complex queries compared to Snowflake. This is the only factor where Snowflake lags behind competitors in the market.

I have been using this solution for four and a half years. 

This is a scalable solution.

The customer service and support for this solution is good. We had previously failed to retrieve data after the time travel period. We had to raise a ticket with technical support team and they helped us. They charged us for this but were able to help us retrieve it.

Positive

The initial setup is straightforward. The beauty of Snowflake is that you can select the configuration you need. For example, if you have a requirement of a one terabyte load with high availability and 10 users, Snowflake will set it up for you to match these requirements. 

The ROI you receive using this solution depends on your use case and if you are starting from scratch or migrating from a legacy system. We have experienced a 40 to 50% improvement in ROI compared to legacy systems.

When using Snowflake, you pay based on your usage. They calculate how much CPU has been used. If you use excess warehouse storage, you are charged one credit per hour. If you are in Asia, you are charged $3 per credit. If you have 10 users running parallel with the same excess, you will be charged $30. 

Pricing for storage is calculated in the same way. You will pay upfront for the storage that you know you will need to consume. There is this option of prepaid consumption as well as post paid consumption. If you pay upfront, you will charged $20 per hour, per terabyte. If you paying after use, you will be charged $40 per terabyte.

There is close to zero maintenance required for this solution. 

You don't need to use traditional warehouses, vacuuming or indexing. A database administrator or system admin is not required.

I would rate this solution a nine out of ten.