Easy button to
ingest & manage
high-scale data in
Iceberg logo

Enjoy the cost savings and shared access of a cloud-native lakehouse, without the engineering pain.

27 Trillion rows


50 PB


35 GB / sec

peak throughput

Build, monitor & share

Give your business an edge with up to the minute data! Easily ingest data from operational stores to the warehouse and Apache Iceberg-based lakehouse with minimal configuration.

Zero-ETL ingest data at scale

Transform with declarative SQL

Observe metrics in real-time

Share with the open ecosystem

Leave the plumbing to us

Upsolver continuously analyzes and optimizes your data movement jobs and lakehouse tables with:

Unify data in motion and data at rest

A single platform for developers to ingest, transform and load streaming and historical data

Resiliency without compromise

SyncStream technology

Synchronized pipelines ensure consistent and reliable processing of real-time events, with late-arriving events automatically accounted.


Systems are unpredictable. In case of network downtime, Upsolver automatically reconnects and restarts operations where it left off.

Automatic schema handling

Column names and data types evolve with your application. Upsolver automatically adjusts names and types to fit the target system, even JSON nested ones.

Exactly-once delivery

Automatically deduplicate events over large windows of time, at scale. Works with streams and files without compromise.

Managed scaling

Built on a decoupled shared-nothing architecture, scales seamlessly to match usage. Utilizes discounted Amazon EC2 Spot instances to save you money.

Data replay and backfill

The need to fix your data is inevitable. Upsolver allows you to easily replay data from any historical point in time or create jobs to backfill existing tables.

Designed and priced for scale

Upsolver charges by data volume. Competitor charges by ‘active rows’.
This key difference drives order-of-magnitude savings when data volumes scale

upsolver designed and priced for scale

Empowering the next generation
of data developers

From startups to enterprises


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