Snowflake Analytics Reviews

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. 

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. 

We use Snowflake Analytics for programs where we write stored procedures which are imported into tables and later used for generating reports via reporting tools.

Snowflake Analytics is flexible in nature, allowing for the addition of more data tables without affecting the main structure. It supports scalability by enabling the scaling of resources up and down depending on demand, which is facilitated through cloud computing platforms. 

Snowflake also helps in improving cost savings. Its structure aids in storing, managing, and analyzing large datasets in the cloud, using various relationships like one-to-one and many-to-one, ensuring consistency in the data structure.

Improvements are needed in importing and exporting large datasets to and from reporting tools. A better recording system for tracking changes to the data structure, including user IDs and timestamps, is needed for increased transparency.

I have used Snowflake Analytics for one year.

During the development stage, there were many maintenance issues, however, these were minimized over time.

Snowflake Analytics is highly scalable as data can be added to the structure without necessitating comprehensive changes. It handles scaling effectively, particularly in a cloud-based environment.

We did not need to escalate many questions to tech support compared to other tools, indicating minimal reliance on Snowflake's tech support.

Positive

I have experience with AWS as a cloud data warehouse.

The initial setup involved creating a Snowflake account and installing the ODBC driver, taking a couple of days. Moving from development to production took 24 continuous hours.

Four people were involved, with a lead taking charge, while I supported the task.

By using clones, we allowed multiple teams to work simultaneously on data without affecting the main dataset. This saved time and maintained consistency, though I am not sure about the financial aspects.

The project managers handled pricing. We minimized time requirements by using indexes and constraints. Clones and servers were used efficiently to address cost issues.

Snowflake requires skilled developers, unlike other tools. It is suitable for managing large, structured, and analyzable datasets. 

I would rate Snowflake eight out of ten.

I use Streamlit apps and Snowflake Analytics for analytics, data warehousing, migration, creating reports, and segregation. It is used to create reports for analytics for users.

We don't have to transfer the data as Snowflake's data sharing capabilities allow us to handle data more efficiently. It stands out against the other tools in the market.

The most important feature is the warehouse functionality. Increasing the warehouse size helps cater to large amounts of data without worrying about performance issues.

When we insert data into a large table, it takes a lot of time. This performance issue can be improved.

I have been using Snowflake Analytics for almost four years. I have used it myself.

If you increase the size of the warehouse, the performance is taken care of. It scales well with large data volumes.

We don't handle the price part. However, our customer is happy with our services regarding Snowflake Analytics.

I would recommend Snowflake Analytics, even with the performance issue related to large table insertions.

I'd rate the solution 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 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.

I mainly use Snowflake Analytics for Power BI reports.

Snowflake Analytics' most valuable feature is its inbuilt infrastructure for executing queries, which I don't have to manage based on my data volume as it's taken care of by Snowflake.

End-to-end execution of jobs isn't possible with Snowflake, which means we have to do some customization. Allowing sequential flow of orchestration would be an improvement. In the next release, Snowflake should include direct integration and communication between other cloud systems.

I've been using Snowflake Analytics for over a week.

Snowflake Analytics is stable.

Snowflake Analytics is scalable.

The initial setup was straightforward, and I would rate the process as four out of five.

Snowflake Analytics is a little more costly than Azure.

Snowflake Analytics is more managed than other cloud offerings, which means I don't have to deal with anything happening in the backend. For those thinking of implementing Snowflake, I advise analyzing the cost, your volume of data, and the number of users. If you have a huge demand on these things, I would recommend choosing Snowflake. I rate Snowflake as seven out of ten.

It's primarily used for data migration, platform organization, and advanced analytics. As an Elite Partner, we provide consulting services to various customers.

It's a fast, 100% SaaS data cloud offering, which is unique in the market. Snowflake is available on all three major cloud providers: AWS, Azure, and GCP.

The UI could be more user-friendly.

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

I would rate the stability a ten out of ten. 

I would rate the scalability a ten out of ten. 

The support is very good. The documentation is very robust, a large online community and a dedicated support team is available.

Positive

I have experience with Microsoft Azure. I was working on the on-premises, and I was looking for a SaaS offering, that's why switched to Snowflake. 

Deployment is straightforward as it's a SaaS product. No maintenance required.

Overall, I would rate the solution a nine out of ten. I would definitely recommend using this solution. 

We use Snowflake Analytics for data cataloging, data science, and managing sales development.

It is quite a convenient tool and has a user-friendly authentication feature.

The platform could work easier for AI implementation compared to Databricks.

I have been using the platform for six months.

We have ten Snowflake Analytics users in our organization.

Compared to Snowflake, changing the data and gaining insights from the application development process while working with Databricks is simpler. It has a more user-friendly and accessible toolbox.

I rate Snowflake Analytics a seven out of ten. It is a good and useful platform. I recommend it to others. We can automate data pipelines using it. I advise others to make sure it meets their business requirements.