Snowflake Reviews

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 use Snowflake as a database to store all the data we stream from the source system.

The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power. If I want to change the computation with other tools like Netezza, I would have to add a hard disk to it. With Snowflake, being on the AWS side, changing warehouses provides me with faster execution of my queries.

The real-time streaming feature is limited with Snowflake and could be improved.

Currently, Snowflake doesn't support unstructured data. With Snowflake, you need to be very particular about the type of data in your source systems. It has to be in a proper structure. You cannot push data to Snowflake in any possible way.

I have been using Snowflake for a couple of years.

Snowflake is a stable solution.

Around 400 users are using the solution in our organization.

We previously used IBM Netezza. We switched to Snowflake in 2020 because it provided us control over its scalability and costing model.

The solution’s initial setup is comparatively easier.

Snowflake is a cloud-based, scalable solution that provides strong data security. Handling all the data is much easier in Snowflake, and it has a very nice interface to control user access. The administration of Snowflake is also comparatively easier.

Snowflake is a cost-effective solution.

Choosing Snowflake completely depends on the quantum of data your organization has and the requirements. Snowflake is suitable for someone looking for a scalable and cost-effective solution that provides quick analysis.

Overall, I rate Snowflake a nine out of ten.

In our organization, data is often spread out over multiple on-premise and cloud-based platforms. Snowflake is an agnostic platform, meaning it can be used regardless of which cloud provider we use and can serve as a single source for all of our data. Our use case then is to ensure that all data is located in one place, utilizing Snowflake as the platform.

With Snowflake, productivity can be increased. Snowflake is faster than on-premise systems and allows for variable compute power based on need. We are currently experimenting with ways to reduce processing time from eight hours to six hours or even less.

The vendor claims that the provision of warming sensors quickly enables warmth to compute nodes, which is their Unique Selling Point. From my experience, this has proven to be true.

For the past year and a half, I have experimented with different proof of concept. I have wanted to use Snowflake, however, I have not been able to do so. Microsoft Azure is superior to Snowflake in terms of its machine learning and artificial intelligence capabilities. Snowflake has its own unique products, but Azure surpasses it in those areas. Snowflake can improve its machine learning and AI capabilities.

I have been using the solution for one and a half years.

I found that Snowflake is highly stable, which is a reflection of the quality of its network.

I have gone to the extremes from a scalability perspective and I give Snowflake's scalability an eight out of ten.

As a premium customer for all these solutions, we have received excellent support overall with no issues encountered thus far. However, it is possible that some users of the free version may be experiencing some issues. I cannot confirm this, but from my experience, there have been no difficulties.

I give the initial setup a seven out of ten for ease and time required.

We are leveraging Snowflake, a cloud-based platform, both independently and in collaboration with the vendor. Our objectives for utilizing Snowflake are distinct from those of the vendor.

Comparing Snowflake to on-prem options such as Oracle or SAP, it seemed more cost-effective. With Vantage, a one-time purchase allows for use as many times and to a large capacity, whereas Snowflake, Azure, and similar services become increasingly expensive as the scale increases. Determining the best point of cost-effectiveness requires further study.

I have tested all the different alternatives to Snowflake as well. It is hard to determine which one is the most suitable, as each has its own advantages and disadvantages.

I give the solution an eight out of ten.

Deciding between Azure Synapse and Snowflake can be difficult, as the best choice depends on one's own use case. Ultimately, it comes down to the available connectors; the product with more connectors is likely the better option. When making a decision, one should consider which other sources they would want to get data from and where they want to send data to. This can help inform their product selection.

Snowflake is used for data warehousing.

The most valuable features of Snowflake are its performance and power.

Snowflake could improve if they had an Operational Data Store(ODS) space.

I have been using Snowflake for approximately four years.

The stability of Snowflake is good.

The scalability of Snowflake is very good.

I have approximately six customers using this solution but in addition, I am directing more.

The technical support from Snowflake was poor previously, they have improved significantly.

Snowflake has an easy setup and it is quick.

There is a license needed to use this solution. There are a few licensing options available. They have a pay-as-you-go option, but it is recommended to pay upfront.

I would recommend this solution to others.

I rate Snowflake a nine out of ten.

We implement this solution for our customers. It is a cloud data warehouse. It is SaaS, and it can be run on Azure, AWS, or something else. We are using its latest version.

It is a very good platform. It can handle structured and semi-structured data, and it can be used for your data warehouse or data lake. It can load and deal with any data that you have. It can extract data from an on-premises database or a website and make it available in the cloud.

It has very fast implementation and integration as compared to other solutions. There is no need for the DBA to manage or do the day-to-day DBA tasks, which is one of the greatest things about it.

In future releases, it can also support full unstructured data.

We have been using this solution for a year.

It is stable.

It has very good scalability. Your data can grow in the platform. We have at least 50 users of this solution in an organization.

Their vendor is wonderful. I only have good words for them.

It is not too complex. Its implementation is easy even for those people who don't know Snowflake and are coming from other environments, such as Oracle or SQL Server.

It can be implemented very quickly. Our customers in Israel implemented it very quickly. It was much faster to implement than other platforms.

It is on a monthly basis. It is based on your usage. There are no additional costs from the point of the licensing fee.

We do give some kind of evaluation to the customers about how much it is going to be. You can decide in Snowflake the virtual machine that you are using for customers. There are several kinds of virtual machines that you can use. It is similar to the clothing sizes: small to extra large. If you need more power in the coming month, you can decide in advance and take a more powerful machine. You can just select it from the platform. You can also decide which machine you want to take for extracting data.

I would advise others to check themselves how fast its implementation can be and how responsive it is. I would also recommend evaluating it before choosing other solutions, such as Microsoft Synapse or Amazon Redshift. You can test it yourself by using a test case. You can try to load the data on each platform, which can take a few weeks, but you will get to know the advantages of this solution. It is very different from other solutions.

I would rate Snowflake a nine out of ten.

I mostly build or design data warehouse analytics solutions using Snowflake.

The productivity across the teams that use Snowflake I believe is higher than it would be without the solution.

Snowflake has three great features: Snowpiping is proving to be very valuable, Time Travel is excellent, and Snowpipes are another great functionality the solution has made available.

Snowflake needs transparency over costs and pricing.

I have been using the solution for three years.

I give the stability an eight out of ten. We rarely have issues.

I give the scalability an eight out of ten.

I have used many on-premise solutions in the past and also Azure Synapse Analytics.

The initial setup is straightforward. I give the setup an eight out of ten.

A basic implementation is quick and we only have to set up Snowflake and the cloud service. We need one engineer and one designer for the implementation.

Depending on the complexity of the implementation, we may need to use a third party or help from the vendor.

Part of the problem with the pricing is that it is very difficult for businesses to get an idea of how expensive it might be until they actually start using Snowflake. Until they start pushing large amounts of data through, we will not really know. I believe that it is very difficult for businesses to make a commitment.

I give the solution an eight out of ten.

My advice is to start Snowflake and not spend too much time thinking about how we could use the solution or what it could be used for. The key is just getting started.

We're using Snowflake for Power BI Cloud. We had a cloud version of Snowflake, so we were connecting to the Snowflake database and importing required tables into our system, Power BI Desktop. From there, we linked those tables and created a semantic layer, an internal layer between the frontend and backend, and then we tuned the data. Then we used both the tables to tie into the dashboards that we developed. The dashboards show the sales information or marketing information.

It's a cloud solution.

I like the entire database. This is the advanced version of the cloud version, so it's really a flexible tool. If you have it implemented at home, you can access it from anywhere.

Sometimes when I'm trying to refresh the data, my different application or tool has to connect to its backend database through the connection I create. Sometimes, I face some issues like not having permissions. These aren't as crucial, but there are common errors sometimes where the database is down, or a table is nullified and a new table is added and you are not given access to that. With those errors, you don't have permissions.

I have been using Snowflake for a year.

It's stable.

The scalability is good. It handles a lot of data, and the processing speed is very high.

It's straightforward. You have to have a rule, database names, and a schema name.

When somebody deploys it and gives me the URL and the required tables to use, I use the URL and configure it from the frontend side, reporting side that could be more like Power BI or Tableau, and I start using it.

I would rate this solution 8 out of 10.

Snowflake is a real-time and cloud-based complete ETL tool. You can receive the beta from various sources from Amazon. You can run your reports and do analysis in  Snowflake. Informatica and Tableau should have done this. Snowflake is a modern version of Informatica which is 100 percent in the cloud.

Snowflake has a variety of other ETL provisions that they provide. You can use your own ETL pipeline. Additionally, they provide adapters, and they are always evolving, it is a well-developed solution.

Snowflake has to build more capabilities because they have only built very few adapters, but they're growing and they're building. They should provide provisions to collect ETL pipeline capabilities, reduce developer work, and make more rapid application development, rather than some customizations. There are very few options, but they are building. I hope they will build ETL rapid application development provisions with more variety.

I have been using Snowflake for approximately eight months.

Snowflake is highly stable.

Snowflake is a cloud solution that provides great scalability. However, I am not sure if it is cost-effective.

We have approximately 30 engineers using this solution. We have plans to scale our usage in the future. This is going to be a futuristic solution.

We have not had any problems with the technical support.

The initial setup of Snowflake is straightforward. To set up the ETL pipeline, pull the data, and then generate the reports takes approximately two hours, end to end.

I did the implementation in-house. We have a three-member team that does the maintenance of Snowflake. However, the amount of people needed depends on the size of the pipeline.

Snowflake licensing is more flexible and it is cheaper than other solutions. I can use it for only 10 days for MVP, or three years, and for flexible models. I can scale up, or down, and the pricing is based on the volume and duration. There are many licensing permutation combinations available.

I rate Snowflake a nine out of ten.