Upsolver

About Upsolver

Upsolver’s data lake platform helps simplify the process for developers to integrate, manage and structure streaming data for analysis, whether on-premises or in the cloud. With a set of advanced stream processing algorithms and an intuitive drag & drop interface for data preparation, Upsolver provides users with the analytical capabilities of a database to stream data into analytics, at the scale of a data lake.

Using no-touch data integration and management tools, Upsolver has the ability to streamline data integration between all major input and output platforms to and from existing S3 data lakes, as well as handle underlying file management and optimization on AWS S3 automatically. Users can get data streams from Kafka / Kinesis to S3 with no data loss or duplications and at any scale, connect to an existing data lake or bucket on S3, and deliver columnar data to SQL engines such as Impala, Athena, and more. Automated file management on AWS S3 helps improve S3 performance by compacting small files together and dividing big files, as well as S3 data freshness using a managed hot-cold architecture. Upsolver enables users to partition data by event time, as well as handle late events, and seamlessly replay data from S3 to incorporate additional fields.

Upsolver’s data preparation tools help get streaming data ready for analysis with fast in-memory data processing at any scale, with data pre-aggregation in-flight. Users can enrich data using multiple out-of-the-box functions or Python snippets, work with nested JSON without manual wrangling, as well as join between data streams and enrich with historical data in-flight.