| Sr Analytics Engineer at Itau Unibanco S.A. | 4.5 | I've found AWS Lake Formation greatly improves our data mesh structure, enhancing governance and integrity, though shared access in our unit poses minor security concerns. It's stable, effective, and I’d rate it 9 out of 10 overall. |
| Co-Founder & CTO at Photios AI | 4.0 | I’ve used AWS Lake Formation for years and found its fine-grained access control and centralized governance valuable, though onboarding was complex. Despite minor performance lags, support was strong and integration made sense for AWS-centric enterprises. |
| Senior Data Engineer at Kaiser Permanente | 4.0 | I use Kafka, Flink, and Spark for real-time healthcare and IoT pipelines, appreciating features like event time processing and auto-scaling, while suggesting improvements in access control, recovery times, and data security. Overall, I rate this solution 8/10. |
| Senior Engineer at Westpac Institutional Bank | 4.0 | I used AWS Lake Formation to help a government client build a secure, scalable data lake with fine-grained access control, leveraging IAM integration, Glue workflows, and LF-Tags, though Athena's query experience could be improved. |
| Senior Software Engineer at a computer software company with 5,001-10,000 employees | 4.5 | I've been using AWS Lake Formation for managing our data lake on AWS, finding the integration with IAM and Terraform smooth, though initial Athena costs were high, and simpler, lower-cost querying options would improve the experience. |
| Full Data Engineer at a financial services firm with 10,001+ employees | 5.0 | I primarily use AWS Lake Formation for data warehousing due to its strong integration, real-time logs, and FinOps benefits, though it could improve in analytics; setup is straightforward, and overall, it significantly boosts data-driven efficiency. |
| Sr. Data/Analytics Engineer at a media company with 5,001-10,000 employees | 3.5 | I used AWS Lake Formation mainly to manage permissions in Glue and Athena, appreciated its visibility features, faced challenges with cross-account sharing, found setup and scalability easy, and would recommend using LF-Tags for better access control. |
| Data Solution Architecht at a tech services company with 1,001-5,000 employees | 4.0 | I implemented AWS Lake Formation to support decentralized data science teams, enabling secure, scalable collaboration, though setup complexities and poor support hampered progress, especially with permissions configuration and frontend-backend integration for access management. |
