Snowflake Analytics Reviews

We have chosen Snowflake to meet customer expectations. Some customers expect a partnership, while others primarily use migrations. They are using streaming data from an on-premises tool. The customer uses an existing system and partners with on-premises partners; we migrate them into the cloud system.

We migrated from Oracle and Zoom to Snowflake using the AWS Group.

One of the key advancements in Snowflake Analytics is data sharing. There are real-time data and survival protection data. If you want the same data, you have to migrate it. You have to move it over to the other place. So, you can now have a copy of the data. You can use it for UAT and development activities.

The backup features are a major aspect of our use of Snowflake for streaming processes. It plays a significant role in our migration process due to the need to export customer data. While the existing system operates primarily in batch mode, the migration process for exporting customer data can now be accomplished using a streaming process.

Implementing everything on-premise is challenging because it require proper support from advisors, DBAs, and others. However, with cloud implementation, there are fewer technical barriers.

I have been using Snowflake Analytics for over a year.

The product is stable.

I rate the solution's stability as seven out of ten.

Our customer's daily transaction data amounts to 75 million records. Previously, we worked with the same customer using a red chip. They're using automatic node increase. We spend a lot of money for the storage activities.

The problem has been completely sorted out with auto-scaling. It automatically adjusts the storage capacity, which means the customer doesn't need to overspend, particularly on storage.

We have proper support. It analyzes user greetings and reports and addresses the issue.

Neutral

We are using the vendor or tenant. We can automatically connect to a source system. There are different connections available. Default connections are deferred. There are multiple source system connectors. We can use those connectors to pull data from various source systems, whether on-premise or in the cloud. Previously, the job was to use the existing built-in character to pull the data, do some budgeting, perform more strategic actions, and load it into the attack.

Initially, we need to set up applications and other necessary components; then, it becomes easier to migrate other things. On-premises setups are more rigid, making deviating from the initial plan challenging. Therefore, we cannot proceed with that approach. Instead, we can opt for the CACH model, which focuses on development and implementation, particularly in the latest tools and technologies.

Snowflake Analytics’s technical and domain aspects are crucial. Both are the most important for improving other products and adding customer value. In such cases, even a few customized elements can take us far. We have some use cases in the requirements we implemented in the process. So, we are using various technologies. The most important things we need to build are customer tools.

Many new features have been added to Snowflake, making it a completely cloud-based system. It's a modern data warehousing solution that incorporates many new technological aspects. 

I recommend Snowflake. If you opt for the red chip, you'll have to spend more on storage. You can avoid these additional costs. It supports data injection and retrieval from various sources, ensuring rapid integration. It offers seamless transition support if users migrate to other platforms like Azure or AWS. There are no limitations on promoting various concepts.

Overall, I rate the solution a seven out of ten.

We use the product for revenue analytics.

Snowflake Analytics opened up larger possibilities from a business perspective for our organization. Its virtualization feature has helped us significantly.

The product's valuable feature is an ease of use. It can run complex workloads with varied compute.

The platform's data governance space needs more capability. There could be AI-driven features and human interactive queries, i.e., natural language queries rather than standard SQL.

We have been using Snowflake Analytics for a few years.

I rate the platform's stability a ten out of ten.

We have around 500 Snowflake Analytics users in our organization. It is a scalable product. We continuously increase the usage as our business expands.

The technical support services are good. However, there could be knowledgeable support and faster response.

Positive

The initial setup was easy. The initial sandbox workload was up and running within a day. The additional configurations related to single sign-on took less than a week to complete.

We have all essential implementation tools available in-house to deploy the product. We do not require any external deployment packages.

The product's pricing is subjective. Snowflake operates on a credit basis. Thus, we can get licenses on pre-purchase credit. We get better discounts on larger purchases.

We explored a few products before.

I rate Snowflake Analytics an eight out of ten. If there is a good amount of data sharing, Snowflake is the right platform. I advise others to start with a small amount of data and then optimize it to set up the right data size.

We use it for tasks related to aggregate functions and statistical analysis.

I appreciate its straightforward interface. The platform not only provides ease of use but also stands out for its speedy execution, conveying a sense of robustness and reliability that I find appealing.

One notable absence in Snowflake's offerings is an on-premises solution.

I have been working with it for one year.

I would rate its stability capabilities nine out of ten.

It offers excellent scalability. I would rate it ten out of ten.

I've also had experience working with Redshift and databases from Microsoft. 
I have a decade or more of experience working with Microsoft, and after such an extended period, there's a natural inclination to explore something different and try new things.

The installation process is seamless. You can create an account and instantly begin working since the platform is readily available on the cloud. This ease of access is particularly advantageous for beginners.

I have been using free trial version.

I would recommend it. Overall, I would rate it nine out of ten.

Our customer use cases vary. Some are doing AI models to pick up trends in the telco, finance, or insurance sectors. Our insurance clients use it more as a data warehouse or data lake for their customer data.

It's the ease of use and the speed with which you can get access to the data. That's really what's added a lot of the value.

It's cloud-based technology, so they can spin it up a lot faster. It's quick and easy to use, quite flexible, and meets all the requirements for a data lake and data warehouse. You don't have to go through the old-school, long process to get a data lake or data warehouse going. I think the main important thing is that you can easily share data from Snowflake.

The elasticity and the scalability are quite valuable. And also, the ability to manage the cost.

Snowflake Analytics should probably have more built-in tools for master data management, data purification, and enhancement. Instead of using third-party tools, it would probably be good if it could be internal to Snowflake.

So, to have integrated capabilities for master data management.

I have been using it since 2021. I work with the latest enterprise edition, AWS version.

I would rate the stability a ten out of ten, where one is low and ten is high stability.

I would rate the scalability a ten out of ten, from one to ten, where one is low, and ten is high scalability.

We've got four clients in South Africa that are using it. One is medium, and the other two are enterprise.

The internal support is really good. They do obviously rely on partners like us to service the client. So it's a good mix of partner and Snowflake to provide the support.

Positive

I would rate my experience with the initial setup of Snowflake Analytics nine out of ten, where one is difficult, and ten is easy to set up.

If your models are not set up efficiently, you could end up with performance and cost issues. So, you need to use the Snowflake expert reviews to ensure your models are optimal. So you have to be wary of that.

It's only on cloud. It takes a few hours to deploy it, regardless of the size of the company. 

We do follow the Snowflake guidelines and process, but our approach to our use cases and projects is an agile methodology.

It's value for money.

I would rate the pricing of Snowflake Analytics a two out of ten, where one is cheap, and ten is expensive.

Especially when compared to competitors and what they offer, the pricing is good.

Users pay for credits. It's on a consumption basis.

Snowflake facilitates AI-driven projects for our customers.

Overall, I would rate it a ten out of ten, without a doubt. I think when it gets to cloud data warehouse and data sharing, it's the best.

We primarily use the solution for database analytics. We can use it for various things, including structured and voice data. We also have a Microsoft SQL server for ONTP we combine and manage all data. We get a data map and have a data layer. For reporting, we use Power BI.

Snowflake is a bit different from a traditional Oracle or Microsoft database. There's a different user access methodology. It's very flexible and gives you good data visibility. You can push back the data one week, one month, or one year.

We can store unstructured data formats and create columns for everything and analyze the data via graphs. You can create pie charts and various visual graphs to study your data. We can't do this type of visualization with any SQL server or Oracle database.

There is very good granularity. The solution scales well. At the end of the day, you can use and effectively manage all of your big data. 

The data-sharing capabilities are good. You can access the data and share it in one click. If you want to share it, for example, with Oracle (if you use it), you can export data to it and share it. You can also use email or other methods. You can manage and share across various schemas. 

Its performance speed is very good. There's no limits to the amount of data you can take on. 

I haven't noticed any limitations with the solution. 

There could be more analytics. We find that IBM has a lot of pro data analytics that we use. 

The distribution methodology isn't as strong as Bethesda or SAP HANA. It's not as strong as other competitors.

I've used the solution for about a year.

The scalability and flexibility are excellent. This is very important to have in a Snowflake database. 

Everything works fine, therefore, I haven't had much content with the technical support team. 

I do not have any information in regards to ROI. I'd need more time with the solution. 

I'd recommend the solution to other users. 

I would rate the solution nine out of ten. 

I use the solution in my company for the real estate and housing industry. The tool is also used in the CPG industry.

The benefits that my company has experienced from the use of the product stem from the fact that it is easy to maintain the platform. The most important part about the product is that it is designed with the help of SQL, so users need not have a specific skill set to run the product. Any person with knowledge of SQL can easily use the product.

The most significant feature of the product that has an impact on data analytics stems from the fact that the tool offers functionalities to help users with data warehousing and AI features. The features of the product are available in such a way that there is a separation in the nature of the computation and storage part the tool offers, making the overall tool very fast. The product is easy to use since it uses SQL or structured query language. Most of the people or technicians in the market are comfortable with SQL or structured query language, making it a tool that is easy to use and understand since it is easy to learn about the solution. Developers or programmers with knowledge of SQL can easily move to Snowflake Analytics, as the product comes with a simple learning curve.

The tool needs to introduce a desktop client so that users can handle the design part, as it is one area where the product lacks and needs to improve. Instead of having to visit the product's web portal, the tool should be installed on a desktop client through which users can indulge in the development process on their local systems.

The product's cost is an area of concern where improvements are required. One part of the cost is attached to the product, and the other part is attached to the solution provider. There should be more transparency provided to users, stating which costs are attached to the product and the prices managed by the solution provider.

I have experience with Snowflake Analytics for five years. My company has implemented the product for some of our clients.

Stability-wise, I rate the solution a nine out of ten.

A lot of features are offered under different tools from Snowflake Analytics. Recently, the product has started to use Python language, along with other languages like SQL. Users need to rely on and use the cloud to carry on with the development phase attached to the solution.

Snowflake Analytics offers the same amount of scalability as the other solutions in the market because it is a tool that is available on the cloud. Scalability-wise, I rate the solution a ten out of ten.

My company deals with around six to seven customers of the product.

I would say that around 100 people use the tool.

There is a different team in my company that connects with the solution's technical support.

The product's initial setup phase is easy in the areas of development and implementation.

The product's deployment phase needs users to follow the standard procedures used under the CI/CD deployment process. You can design it with the help of the CI/CD deployment process. The deployment process is simple.

The solution is deployed on the cloud.

The product's licensing cost varies depending on the models and different structures offered by the solution. I feel that the cost of the product is fine. I rate the product's licensing cost a five or six on a scale of one to ten, where one is low price, and ten is high price.

The product is useful in areas like data warehouse and data analytics since such functionalities of the tool are widely used by my company's clients.

Considering the ease of use that the product provides to support my company's teams' daily operations, I would say that the tool offers help in the area of projects and support.

The product handles data security and compliance areas by providing high security as the tool offers container services, making it highly secure for users during data sharing. The users can have permission authority, without which others cannot see the data that is highly secured within the container.

I recommend the product to those who plan to use it.

The product is easy to scale out. The solution is available on the cloud, and its basic development nature falls under the SQL side, which is something that makes it favorable for development teams across the world. It is easy to learn about the product and start working on it, meaning it has a simple learning curve.

I rate the overall tool a nine out of ten.

I use the tool for data warehousing, analytics, and machine learning.

The most valuable feature of the solution Stems from the fact that the tool offers a virtual warehouse along with multiple other features.

Snowflake's Snowpark is an area of concern where improvements are required. Snowflake's Snowpark is a pretty new concept. Snowflake's Snowpark should improve my adding new libraries and getting the codes deployed quickly.

I have been using Snowflake Analytics for more than five years. I am an end user of the product. I am also a developer who builds platforms for others with the help of Snowflake Analytics. There is no version of the product in general, as it is a full-fledged product.

It is a stable solution. Stability-wise, I rate the solution a ten out of ten.

The scalability of the product is pretty good. It is a highly scalable product. I rate the product's scalability a nine out of ten. Users can scale up or scale out the solution.

I use the solution daily in my company.

Presently, there aren't many uses of the solution in my company. In the future, I believe that the number of users of the product in my company will increase.

My company is in contact with a technical person from Snowflake Analytics, who helps us. I rate the technical support a seven or eight out of ten.

Positive

I have experience with Oracle, Microsoft SQL Server, and AWS.

My company started to use Snowflake Analytics since we did not want to have an on-premises product. Snowflake Analytics was also cost-effective for our company.

I rate the product's initial setup phase an eight or nine on a scale of one to ten, where one is a difficult process, and ten is an easy process. The setup process is straightforward.

The deployment requires users to have an account, and since it is a SaaS solution, Snowflake Analytics manages all the Infrastructures based on which the tool provides the user login details. The user creation is also pretty smooth with the product, so a user can start using it quickly.

The solution is deployed on the cloud services offered by AWS.

The solution can be deployed in a week, along with the licensing part.

For the deployment of the product, one architect from Snowflake, one person from AWS, and two admin developers, are required.

For my current project, a third-party involvement was there in the installation phase of the product. Previously, I was involved in the product's installation process, which involved the licensing part and setting up of the environment.

I rate the product price a seven on a scale of one to ten, where one is low price, and ten is high price. There are some additional costs based on the number of users or data warehouses.

Against Snowflake Analytics, my company has an option called Databricks. For our company's primary use cases, we prefer Snowflake Analytics.

Snowflake Analytics has supported our company's data warehousing and analytics part by helping us reduce our overall costs involved in such areas. The product also offers a better performance than the on-premises tools that are available.

Snowflake Analytics has improved our company's data-driven decision-making processes since the go-to-market timeline has been reduced with the use of the product. Earlier, the go-to-market timeline was such that my company used to take over a month to get new data for the end users. My company can get the data within a week or before, allowing users to use it for their analytics. The tool has reduced the go-to-market timeline.

The benefits from the product's scalability and performance features stem from the fact that it helps with the costs and reduced go-to-market timeline to get things up and ready for the end users, which is drastically much less than what the on-premises products offer.

The product's maintenance can be taken care of by two people.

The scalability of the product has impacted our company's data-driven decision-making since I have a lot of data with me currently. For initial loads, my company uses small warehouses, but after a while, it will be big warehouses. Based on the aforementioned details, my company makes data-driven decisions, like how much warehouse size we need or whether we need to scale up or scale out.

Snowflake Analytics is better than the other platforms that work on either a cloud or an on-premises version. Snowflake Analytics can improve in areas like scalability and in the way the queries are written.

Snowflake Analytics is pretty easy to use with the connectors for integration with the tools and systems in my company.

Others who plan to use the solution can benefit from it. I recommend others consider or try out a PoC phase or exploration process of the product to see whether the tool fits their use cases.

I rate the overall tool an eight out of ten.

It is a cloud data warehouse. We use the solution in our organization for setting up data warehouses, building tables, and querying from the tables.

The product lets us build tables.

Time Travel and Snowpipe are good features. The rest of the features are standard.

The tool must provide better machine-learning functionalities.

I have been using the solution for five years. I am working with the latest version of the solution.

The solution is fairly stable. It doesn't crash. We don't get any incidents in Snowflake. I rate the stability a ten out of ten.

I rate the product’s scalability a six or seven out of ten. Scaling costs a lot of money. It could be improved. Less than ten users use the product in our organization for demo purposes. We use it once a month. We do not have plans to increase the usage in the future.

The technical support is not very good. I rate the support a two or three out of ten. The tool does not provide a straight support line that we can use unless we're a very big partner. It's very hard to get support from the team. We have community support, but it's not good for big incidents.

Negative

We also use BigQuery and Redshift. We have different customers that use different data warehouses. We use Snowflake when our customers advise us to use it. Snowflake is more stable than BigQuery.

The tool is quite easy to set up. I rate the ease of setup an eight out of ten. It's a cloud-based solution. We're partners of AWS, GCP, and Azure. We use all three of them. It takes half an hour to deploy the solution. To deploy the product, we must create Snowflake accounts and set it up with the cloud provider of our choice. Then, we get an email with our access to Snowflake, and we can start using the data warehouse and do anything with it. It's quite easy to use.

The deployment can be done in-house. We need one person to deploy the tool and two or three people to maintain it. People maintaining the solution monitor the costs and ensure the warehouse is the right size.

The product must improve its pricing model. We must scale it up considerably to get a good value. The tool is quite expensive. The product must provide a pay-as-you-go pricing option. I rate the pricing an eight out of ten. If we run big workloads in Snowflake, it will be more expensive than both BigQuery and Redshift.

People considering the solution must evaluate it against all the other options to see whether they need to use it. They must look at the alternatives depending on their cloud provider. If they're on Microsoft Azure, then Snowflake is the best option. However, if they're using Google Cloud, they should consider BigQuery. If they’re on AWS, they must consider Redshift. The tool has helped us with a few customer case studies. Overall, I rate the product a seven or eight out of ten.