Frictionless Data Lake Ingestion and ETL
Prepare streaming and historical big data for analysis using a visual platform and SQL, at the scale of your AWS data lake.
Upsolver was built from the ground up to unlock the business value of event streams, with a cloud first architecture that empowers data consumers to be self-sufficient with streaming data and data lakes.
Why choose Upsolver?
Upsolver is built to run natively on any AWS account by decoupling storage on S3, compute on EC2 and metadata management in Glue Data Catalog. Queries in Athena, Redshift Spectrum and other analytics tools run 100X faster since Upsolver automatically optimises S3 with columnar file formats, partitioning and compaction.
“Upsolver lets me handle data lake operations in my spare time. It’s that easy.”
- Guy Boyango, CTO, Sisense
“Upsolver lets us focus on features rather than infrastructure and pipelines.”
- Seva Feldman, VP R&D, ironSource Mobile
“We launched our real-time data architecture in weeks, which saved us 24 months of engineering.”
- Amit Attias, Co-founder and CTO, Bigabid
“We transitioned from a data warehouse to a fully operational data lake in 3 weeks.”
- Alon Horowitz, VP R&D, Meta Networks
Customer Stories
Easy-to-use
Save thousands of engineering hours with a visual interface and auto-pilot management.
Robust
Deliver advanced analytics by combining event streams with historical big data in real-time.
Accessible
Make all your data available for near real-time analytics and real-time applications.
Elastic
Add as much compute power as needed for scale and isolation between workloads using a fully decoupled architecture.
Reliable
Avoid data loss and duplication by using exactly-once processing at every step of your data value chain.
Open
Let users choose their own analytics tool (AWS Athena, Presto, Spark) by storing data and metadata in an open format within your cloud account
