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 solution has many features that are applicable to events such as audits."
"It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services."
"We use AWS Lake Formation typically for the data warehouse."
"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 is quite good at handling analytics. It's done a good job at helping us centralize them."
"The features that I have found most valuable are the ease of use, the rapidness, how quickly the solution can be implemented, and of course that it's been very easy to move from the on-premise world to the Cloud world because Snowflake is based on SQL also."
"The most valuable feature is the snapshot database. In one second, you can just take a snapshot of the database for test purposes."
"Snowflake is an enormously useful platform. The Snowpipe feature is valuable because it allows us to load terabytes and petabytes of data into the data mart at a very low cost."
"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."
"The thing I find most valuable is that scalability, space storage, and computing power is separate. When you scale up, it is live from one second to the next — constantly available as you scale — so there is no downtime or interruption of services."
"Great scalability and near zero maintenance."
"The tool is very easy to use. The solution’s desktop features are also very easy to use. Also, the product’s SQL-based connectivity is also good. It can connect with any tool."
"Working with Parquet files is support out of the box and it makes large dataset processing much easier."
"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."
"For the end-users, it's not as user-friendly as it could be."
"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."
"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."
"AWS Lake Formation's pricing could be cheaper."
"We would like to have an on-premises deployment option that has the same features, including scalability."
"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."
"We would like to be able to do modeling with Snowflake. It should support statistical modeling."
"It's difficult to know how to size everything correctly."
"Snowflake needs transparency over costs and pricing."
"In future releases, it can also support full unstructured data."
"The UI could improve because sometimes in the security query the UI freezes. We then have to close the window and restart."
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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