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Instantly Query Kinesis Streams in Amazon Athena

Automate 100% of the effort of preparing your streaming data for Amazon / Redshift Spectrum / Presto / SparkSQL and start analyzing streams in Kinesis in minutes.

Minutes to create or change tables that are updated in real-time

Data latency <10 minutes

85% lower total cost of analytics infrastructure

Upsolver lets you build an end-to-end streaming data pipeline in mere minutes. You don’t need to write Scala, be an expert in Apache Spark, or waste previous engineering resources on manual ETL.

Simply connect to your streams, build your tables with drag-and-drop and run your queries - it just works. Upsolver will auto-magically optimize everything from compaction to partitioning, ensuring your queries cost less and run faster.

Key Features

Visual self-service for data consumers - manage and query your data lake as if it was a database

Up to 100x better query performance compared to home-grown ETL using techniques like compaction, columnar formats and partitioning

All data is stored on S3 optimized for consumption - automatic compaction, and partitioning

Effortlessly perform difficult data transformations like joins, deduplication and aggregations on sliding time-windows

Perform update and delete operations instead of being limited to append-only tables


Discover how Upsolver can unlock the value of your streaming data.

See it in action