Cloud data lakes are reliable, scalable and affordable. However, the complexity of writing code and orchestrating pipelines on raw object storage have held data lakes back from having the impact they should.
Upsolver uses a declarative approach based on SQL transformations to eliminates those barriers, so you get simplicity combined with data lake power and affordability.
Continuously deliver up-to-the-minute fresh, analytics-ready tables to query engines, cloud data warehouses and streaming platforms. Even with nested, semi-structured and array data. No more stale analytics based on nightly or weekly jobs.
Process complex, continuous data on your cost-effective data lake for downstream use in your data warehouse. Greatly reduce your data warehouse costs for ingestion, compute and storage. Build pipelines using SQL and automation, reducing your data engineering overhead and time-to-value as well.