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Cloud data warehouses have become the go-to store for business intelligence reporting and ad hoc analytics on structured data. However, cloud data warehouses are built for serving end-user queries on batch data sets. When it comes to continuous data preparation they are too slow and expensive.
Also, they are full-stack solutions that include a closed storage layer and captive query engine, which locks you into a single platform and limits your future analytics options, restricts data availability and stifles innovation.
By using Upsolver pipelines to transform your continuous data on the data lake, you greatly reduce your compute costs while maintaining data freshness for consuming end-users and apps.
No need to hand code ingestion as Upsolver comes with connectors for a variety of data source types:
SQLake is Upsolver’s newest offering. It lets you build and run reliable data pipelines on streaming and batch data via an all-SQL experience.
Schedule a quick, no-strings-attached with one of our cloud architecture gurus.
See how the world’s most data-intensive companies use Upsolver to analyze petabytes of data.
See which data sources and outputs Upsolver supports natively.
Explore our expert-made templates & start with the right one for you.