Put an end to
“garbage in, garbage out.”

The big data ingestion platform that stops bad data
from polluting your warehouse and lake.

5 Examples of Data Quality Problems that Break your Warehouse or Lake - Read Now

Powering over 10,000 Big Data Ingestion Pipelines

The Impact of “Garbage In, Garbage Out”

Big data sources such as event streams, logs and database change events (CDC) pose a constant data quality challenge to transformation pipelines, due to technical issues and human actions that cause late arriving data, out-of-order data, duplicates and frequently-changing schemas.

These data issues create negative impacts such as:

  • Serving incorrect results to data consumers
  • Wasted engineering effort to fix data downstream
  • Complex and fragile transformation pipelines

Solve for Quality on Ingestion

Upsolver uniquely solves the data quality challenge upon ingestion, by enforcing delivery of exactly-once, strongly-ordered data for downstream analytics, and it does it at any scale or data freshness requirement.

  • Data availability – on-time, exactly-once, strongly ordered data
  • Data evolution – drift detection, adapt schema automatically, replay
  • Data cleansing – in-stream filtering and masking of sensitive data
  • Data observability – inspection, profiling, monitoring, alerting

Unbreakable Ingestion
for your Data Warehouse

Eliminate unending quality fixes to your data models.

  • Exactly once, strongly ordered, cleansed ingestion
  • Derisks your downstream models by providing always-clean, deduplicated, ordered data
  • Performs near-real-time ingestion at scale
  • Includes out-of-the-box quality monitoring and alerting

A Fail-Safe Foundation
for your Data Lake

Get trusted big and streaming data with minimal engineering.

  • Safely ingest continuous data at speed and scale
  • Use SQL to transform raw data into silver and gold tables
  • Automate data best practices and pipeline orchestration

Processing Power at Scale

Upsolver leverages cloud infrastructure to economically scale to whatever size you need while maintaining strongly ordered, exactly-once data, real-time cleansing operations and stateful transformations for data lake ETL.

  • Strongly ordered data via unique distributed locking technology
  • Economical elastic scaling on EC2 spot instances
  • Real-time cleansing operations executed in-stream
  • Stateful data lake transformations

No-Code Easy

Whether you’re a data engineer or analyst, you can build ingestion pipelines in minutes using wizards for configuring source, destination, and cleansing operations. Built-in observability ensures that your data is what you expect, and alerts you when it isn’t. Since Upsolver is serverless and cloud-native, you have no infrastructure to manage.

  • No-code development of ingestion pipelines
  • Fully-managed cloud service
  • Out-of-the-box data observability
  • CI/CD enabled

Ingestion built for your architecture


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