Optimize Your Lakehouse Tables

Accelerate performance & reduce costs with data lakehouse table optimizations for Apache Hudi, Apache Iceberg, and Delta Lake

Universal Data Lakehouse hero image

Advanced Tools to Accelerate your Data Lakehouse and Reduce Costs

Accelerate Time to Analytics

  • With minimal configuration updates to your existing data pipelines, uncover inefficiencies and deliver up to 10x faster analytics.
  • Enhance ingestion and query performance of all data lakehouses with table cleaning, clustering, compaction, file-sizing, and more.
A screen shot of a web page with a line graph.
Three screenshots showing the time and date of the event.

Keep Costs Down with Automation

  • Eliminate burdensome manual debugging and maintenance for table cleaning, clustering, compaction, file-sizing, and more.
  • Simply configure a few services and Onehouse will auto-tune your data lakehouse — and keep it tuned.

Observability & Monitoring

  • Track key metrics, dashboards, and pre-built visual insights about your data lakehouse to spot patterns and optimize storage and performance.
  • Understand the state of your pipelines and tables. Track key metrics with pre-built dashboards and receive customized weekly review emails so you can optimize your tables with insights into partitions and data skew.
Two screens showing the notification settings for a website.

Eliminate Manual Tuning and Maintenance

Data lakehouse pipelines require significant manual tuning. Onehouse enables a hands-free approach to optimizing your lakehouse tables.

A screenshot of a web page with a table of services.

Key Features for Accelerated Data Ingestion

A purple line drawing of two hexagonals.

Intelligent incremental clustering

  • By making reads more efficient with incremental clustering, accelerate read performance and reduce overall costs.
  • Configurations include keys, layout strategy, and frequency.
a purple line drawing of two circles

Async compaction

  • Improve write performance with async compaction to merge incoming data into the table. If you are using Apache Hudi, this is particularly useful for Merge-on-Read pipelines.
  • Configurations include frequency of runs and bytes per compaction.
A purple line drawing of a stack of coins.

Advanced cleaning

  • Easily remove old data already committed to a table and beyond your time-travel retention policies to keep storage costs down.
  • Configurations include frequency and time travel retention policies.

Uber’s Universal Data Lakehouse Success


Reduction in pipeline run times


Reduction in ETL time for critical tables

Uber’s journey

Learn How to Optimize Your Lakehouse Tables


Onehouse Managed Lakehouse Table Optimizer Quick Start

download now

Introducing Onehouse LakeView and Table Optimizer - Power Tools for the Data Lakehouse

Watch Now
No items found.

Want to optimize your data lakehouse?

schedule a consultation