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."
"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."
"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."
"Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."
"They separate compute and storage. You can scale storage independently of the computer, or you can scale computing independently of storage. If you need to buy more computer parts you can add new virtual warehouses in Snowflake. Similarly, if you need more storage, you take more storage. It's most scalable in the database essentially; typically you don't have this scalability independence on-premises."
"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."
"It has great flexibility whenever we are loading data and performs ELT (extract, load, transform) techniques instead of ETL."
"It helped us to build MVP (minimum viable product) for our idea of building a data warehouse model for small businesses."
"The most efficient way for real-time dashboards or analytical business intelligence reports to be sent to the customer."
"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."
"It's ultra-fast at handling queries, which is what we find very convenient."
"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."
"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 price could be improved."
"The solution could improve the user interface and add functionality to the system."
"Snowflake has to improve their spatial parts since it doesn't have much in terms of geo-spatial queries."
"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."
"There are some stored procedures that we've had trouble with. The solution also needs to fine-tune the connectors to be able to connect into the system source."
"From the documentation, the black box is not very descriptive. Snowflake does not reveal how exactly the data is processed or sourced."
"If we can have a feature where the results can be moved to different tabs, so that I can compare the results with earlier queries before applying the changes, it would be great."
"These days, they are pushing users towards the GUI or graphical version. However, I am more familiar with the classic version. I'd like to continue to work with it using the older approach."
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 Oracle Autonomous Data Warehouse. See our AWS Lake Formation vs. Snowflake report.
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