Introduce self-service agility to your AWS data lake by making it easy for data consumers to ingest, manage and structure streaming data.
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Create event driven applications on AWS using a simple user interface and stateful stream computations, with fully automated DataOps – pipeline orchestration, scaling, error recovery, replay and more.
Don’t just dump data blindly into S3 – Upsolver’s data lake ingestion tools let you see schema-on-write, statistics and visualization to ensure you’re creating a data lake and not a swamp.
Upsolver runs in-memory over object stores (no local storage) and scales to 1000s of nodes. Queries in engines like AWS Athena run up to 100X faster using Upsolver data.
Operations in Upsolver are translated to SQL and pushed to Git. Data is ingested and stored using open formats like Avro/Parquet.
Output data to your favorite AWS tools and databases – Athena, Redshift, Elasticsearch – to support a wide variety of use cases across your organization.
Your data is only persisted to your Amazon S3 storage, with data processing in public or private VPC.
Discover the 6 crucial guidelines to prepare your data for Athena in this free webinar.
Learn how to avoid common pitfalls, reduce costs and ensure high performance.
Partibest practices you need to know in order to optimize your analytics infrastructure. Get the Guide »
Enforce GDPR and other regulatory compliance by keeping track of all user records in your lake
