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.
"It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services."
"The solution has many features that are applicable to events such as audits."
"The solution is quite good at handling analytics. It's done a good job at helping us centralize them."
"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 querying speed is fast."
"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."
"I like the fact that we don't need a DBA. It automatically scales stuff."
"I like the idea that you can assign roles and responsibilities, limiting access to data."
"Its performance is most valuable. As compared to SQL Server, we are able to see a significant improvement in performance with Snowflake."
"Very easy to use and easy to query."
"The most valuable feature of Snowflake is it's an all-in-one data warehousing solution."
"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."
"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."
"For the end-users, it's not as user-friendly as it could be."
"AWS Lake Formation's pricing could be cheaper."
"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."
"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."
"The cost of the solution could be reduced."
"There are three things that came to my notice. I am not very sure whether they have already done it. The first one is very specific to the virtual data warehouse. Snowflake might want to offer industry-specific models for the data warehouse. Snowflake is a very strong product with credit. For a typical retail industry, such as the pharma industry, if it can get into the functional space as well, it will be a big shot in their arm. The second thing is related to the migration from other data warehouses to Snowflake. They can make the migration a little bit more seamless and easy. It should be compatible, well-structured, and well-governed. Many enterprises have huge impetus and urgency to move to Snowflake from their existing data warehouse, so, naturally, this is an area that is critical. The third thing is related to the capability of dealing with relational and dimensional structures. It is not that friendly with relational structures. Snowflake is more friendly with the dimensional structure or the data masks, which is characteristic of a Kimball model. It is very difficult to be savvy and friendly with both structures because these structures are different and address different kinds of needs. One is manipulation-heavy, and the other one is read-heavy or analysis-heavy. One is for heavy or frequent changes and amendments, and the other one is for frequent reads. One is flat, and the other one is distributed. There are fundamental differences between these two structures. If I were to consider Snowflake as a silver bullet, it should be equally savvy on both ends, which I don't think is the case. Maybe the product has grown and scaled up from where it was."
"The design of the product is easily misunderstood."
"Their strategy is just to leverage what you've got and put Snowflake in the middle. It does work well with other tools. You have to buy a separate reporting tool and a separate data loading tool, whereas, in some platforms, these tools are baked in. In the long-term, they'll need to add more direct partnerships to the ecosystem so that it's not like adding on tools around Snowflake to make it work. They can also consider including Snowflake native reporting tools versus partnering with other reporting tools. It would kind of change where they sit in the market."
"To ensure the proper functioning of Snowflake as an MDS, it relies heavily on other partner tools."
"I can only access Snowflake from the web. It would be better if we could have an app that we can install locally on our laptops to connect to the server without needing to go to the web page. Apart from that, it's hard to point out any limitations in the tool."
"There are always a few operation updates here and there that can be made."
"I think that Snowflake could improve its user interface. The current one is not interactive."
AWS Lake Formation is ranked 12th in Cloud Data Warehouse with 5 reviews while Snowflake is ranked 1st in Cloud Data Warehouse with 94 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 Amazon EMR. See our AWS Lake Formation vs. Snowflake report.
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