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When you query a database, it automatically generates an execution plan. While a data pipeline is just query logic that runs continuously, data engineers are forced to spend countless hours manually building execution plans – a.k.a. coding orchestration DAGs.
Having to manually orchestrate data pipelines leads to:
With SQLake, you use SQL to ingest streams and files into data lake tables and then create jobs which transform, join, and aggregate that data, and stream it into destination systems for analytics consumption.
Learn what’s the best way to design and build a data platform that’s aligned with your use cases.
Understand data lake architecture best practices in this practical handbook for data engineers, data scientists and data architects.
Learn how Upsolver’s technology differs from platforms built on Apache Spark in our comprehensive guide.
Explore our expert-made templates & start with the right one for you.