We compared Snowflake and AWS Lake Formation based on our user's reviews in several parameters.
In summary, Snowflake is praised for its high performance, scalability, user-friendly interface, and efficient customer support. Users find Snowflake's pricing reasonable and appreciate its positive ROI. On the other hand, AWS Lake Formation is lauded for its flexible pricing, excellent data management capabilities, comprehensive security measures, and seamless integration with other AWS services. Users value its efficient setup process and commendable customer service. Areas for improvement in AWS Lake Formation include usability, access permissions management, data processing speed, documentation, data integration options, and customization features.
Features: Snowflake's valuable features include high performance, scalability, and ease of use. Users appreciate its ability to handle large data volumes quickly. In contrast, AWS Lake Formation offers excellent data management capabilities, comprehensive security measures, and seamless integration with other AWS services. Users enjoy the simple setup process and robust access control mechanisms, ensuring reliable data management and efficient workflows.
Pricing and ROI: The setup cost for Snowflake is seen as reasonable and competitive, with a straightforward and uncomplicated process. Users appreciate the flexible licensing terms and options. On the other hand, AWS Lake Formation offers a flexible and cost-effective pricing model, with a straightforward and hassle-free setup cost. Users value the licensing options provided., The user reviews for Snowflake indicate a positive and beneficial ROI. Similarly, AWS Lake Formation also provides a significant ROI with positive results reported by users.
Room for Improvement: Snowflake has room for improvement in specific areas to enhance user experience and functionality. AWS Lake Formation, on the other hand, needs enhancements in usability, access permissions management, data processing speed, troubleshooting resources, data integration options, and feature customization.
Deployment and customer support: The reviews highlight that when evaluating the duration required for a new tech solution, Snowflake users emphasize distinguishing between deployment and setup phases, while AWS Lake Formation users have varying timeframes for deployment, setup, and implementation, suggesting that these phases should be considered separately., Snowflake's customer service has received positive feedback for promptness and effectiveness. Users appreciate the expertise and helpful guidance provided by the support team. AWS Lake Formation's customer service is also commendable, with users valuing their responsiveness, expertise, and commitment to customer success.
The summary above is based on 43 interviews we conducted recently with Snowflake and AWS Lake Formation users. To access the review's full transcripts, download our report.
"The most important advantage in using AWS Lake Formation is its ability to connect the data lake to the other technologies in AWS. This is what I advise my clients."
"The solution has many features that are applicable to events such as audits."
"We use AWS Lake Formation typically for the data warehouse."
"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."
"It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services."
"It helped us to build MVP (minimum viable product) for our idea of building a data warehouse model for small businesses."
"Data Science capabilities are the most valuable feature."
"The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."
"We find the data sharing and data marketplace aspects of Snowflake absolutely amazing."
"Its speed and performance were the most valuable. Easy configuration of Snowflake in any cloud was also a benefit."
"The ETL and data ingestion capabilities are better in this solution as compared to SQL Server. SQL Server doesn't do much data ingestion, but Snowflake can do it quite conveniently."
"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."
"I like the idea that you can assign roles and responsibilities, limiting access to data."
"In our experience what could be improved are not the support, performance or monitoring, but at a managerial level, the very expensive professional services of AWS. This could be an area of improvement for them. It's too expensive to acquire their support."
"For the end-users, it's not as user-friendly as it could be."
"The solution could make improvements around orchestration and doing some automation stuff on AWS front automation. It would be useful if we could use automation to build images and use hardened images which are CIS compliant."
"It falls short when it comes to more granular access control, such as cell-level or row-level entitlements which is a significant drawback for organizations that require precise control over who can access specific rows of data."
"AWS Lake Formation's pricing could be cheaper."
"The solution could improve by allowing non-structured data, such as PDFs, images, or videos. We cannot see the data."
"Snowflake has to improve their spatial parts since it doesn't have much in terms of geo-spatial queries."
"The price could be improved."
"They do have a native connector to connect with integration tools for loading data, but it would be much better to have the functionality built-in."
"For the Snowflake database, there should be some third-party features for the ETL. It would also be good to be able to use some kind of controls to get the data either from another database or a flat file. Its price should be improved. It should be cheaper than Microsoft."
"There is room for improvement in Snowflake's integration with Python. We do a lot of SQL programming in Snowflake, but we go to a different tool to program when we have to in Python."
"It needs a bit more rigor and governance, which is something you don't get with newer tools. This makes it less enterprise scalable. Its governance and structure can be enhanced, which would really be valuable. I would like to see some kind of prebuilt functionality in terms of having almost like a pre-built data warehouse. A functionality for generating automated kind of pieces would be good."
"The aspect of it that was more complicated was stored procedures. It does not support SQL language-based stored procedures. You have to write in JavaScript. If they supported SQL language and stored procedures, it would make migration from on-prem much simpler. In most cases, if an on-prem solution has stored procedures, they're usually written in SQL. They're not written as what most on-prem DBMS would refer to as an external stored procedure, which is what these feel like to most people because they're written in a language outside of SQL."
AWS Lake Formation is ranked 12th in Cloud Data Warehouse with 5 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 92 reviews. AWS Lake Formation is rated 7.6, while Snowflake is rated 8.4. The top reviewer of AWS Lake Formation writes "Strategically aligning data management in a multi-cloud environment with significant reporting challenges". On the other hand, the top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". AWS Lake Formation is most compared with Azure Data Factory, Amazon Redshift, Microsoft Azure Synapse Analytics, BigQuery and Amazon EMR, whereas Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and Oracle Autonomous Data Warehouse. See our AWS Lake Formation vs. Snowflake report.
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