Snowflake Analytics Reviews

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.

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.

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.

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. 

We use Snowflake Analytics to organize data. We create a fact and dimension table, relate it using its cardinality, load it from the source and use it for reporting.

It helps with business intelligence by providing analytics that can be reported.

There are issues while loading data from Snowflake Analytics to the Power BI reporting, and it doesn't get loaded directly. Sometimes we need to use queries to fix it, but it affects our reporting. Snowflake Analytics should be easily loaded into the reporting tool because it is the final end tool.

We have been using this solution for four months.

I cannot speak to stability because our data is not yet 100% loaded. It is a continuous ongoing process.

It is a scalable solution. In my organization, about four people, along with our clients, use Snowflake Analytics. So about four to eight people are using it. So far, it is not difficult to maintain the solution.

The initial setup was straightforward, neat, understandable and clear. We did the deployment in-house.

I do not have details about the licensing costs.

We did not review any other solution before Snowflake Analytics.

I rate this solution an eight out of ten. It is a wonderful tool. It easily organizes data, makes it accessible, loads it from the pipeline and helps with reporting.

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. 

There are a lot of use cases for Snowflake. We can use it to build data pipelines. We can also use it to process terabytes of data to generate real-time analytics.

The computational power of Snowflake is very good. We get results very fast. Snowflake also has very good connectors for building pipelines. It makes it easy to connect to different cloud solutions.

Snowflake should include a WHERE clause for building data pipelines. When we create pipelines, Snowflake does not provide the WHERE clause. So the data transformation does not take place. We have to dump data as it is and transform it into the pipeline. If the WHERE clause is included, it will be very beneficial in the future.

I have been using Snowflake for around two years.

Snowflake is a stable product.

Snowflake is a scalable solution.

Snowflake’s technical support is good.

The initial setup was very straightforward. It is not very complex. If you are building something which requires customized queries or stored procedures, it is a little complex.

Initially, we faced some syntactic problems during setup. Then, there were some concerns about the WHERE clause. Apart from these, we did not face any other problems.

I went through the product documentation and deployed the solution myself. The deployment took one or two days. There were many different phases in the deployment strategy. I joined the team during deployment.

Using Snowflake, we can dump data through data pipelines and generate analytics. I do not belong to the sales team, so I do not know about the pricing information of Snowflake. I rate Snowflake an eight out of ten.