Onehouse - Open Data Infrastructure That Runs in Your Account

Ingest, Transform, Serve. One Platform.

Deploy Onehouse in your VPC or any Kubernetes cluster. Pay as you go, or a flat yearly fee.

Deployment Options

Onehouse in Your Cloud

Deploy the Onehouse Platform in your own VPC, on any cloud

Onehouse in Your K8s

Any managed Kubernetes: Amazon EKS, Google GKE or Azure AKS
Your own Kubernetes, including on-premises clusters
Or a NeoCloud: Nebius, CoreWeave, Nscale, DigitalOcean or Crusoe

Onehouse Platform Components

Capture from Any Source

Cloud Storage

Database CDC

Streaming

Capture from Any Source

Cloud storage: Parquet, JSON, CSV, XML and binary files on Amazon S3, Google Cloud Storage, Azure Data Lake Storage, or any S3-compatible object store
Database CDC: Oracle, PostgreSQL, MySQL, SQL Server, MongoDB, DynamoDB and other NoSQL stores, captured as change streams
Streaming: Apache Kafka, Confluent Cloud, Amazon MSK, Redpanda and Apache Pulsar, read continuously rather than in batches

OneFlow™

Managed Ingestion

OneFlow™ Ingestion

Incremental end to end. Each run reads and writes only what changed, so cost tracks new data, not table size.
Fully managed CDC, streams and files, with lag-aware scheduling that holds your freshness target.

Spark Jobs/ETL

Transform data

Spark Jobs/ETL

Transformation pipelines in SQL, Spark, Scala or PySpark, with no rewrites
Incremental by default, so jobs process only what changed

Lakegres™

Analytics and AI Context Serving

Lakegres™

The analytics and AI serving layer, straight from open tables
A Postgres-compatible endpoint; 2-10x faster than AWS Athena in production

Quanton™ Engine

SQL and Apache Spark

Quanton™ Engine

Run SQL and Spark ETL 5x faster than open-source Spark at 75% lower cost, using your existing tools and libraries, with the Quanton Engine on the Onehouse Compute Runtime.

Onehouse Compute Runtime

Adaptive Workload Optimizer

Serverless Spark Compute

High-Performance Lakehouse I/O

Onehouse Compute Runtime

Our autoscaler right-sizes clusters in minutes, where Spark’s default needs 30-40.
Multiplexed scheduling packs many jobs onto shared clusters, on spot and Graviton.
Vectorized columnar merging and storage access tuned to cut cloud request costs.

Open Table Storage and Optimization

Apache Hudi, Apache Iceberg and Delta Lake in your own buckets, converted in any direction with Apache XTable (Incubating)
Table Optimizer runs compaction, clustering, cleaning and file-sizing continuously, so tables stay fast without a maintenance job to babysit

Deliver Data to Any Workload

Warehouse

Query Engines

AI/ML Platforms

Vector Database

Deliver Data to Any Workload

OneSync keeps table metadata and access permissions in step across Glue, Unity, Snowflake and Hive at the same time, in every format.
Every cloud ships its own catalog. Staying decoupled from all of them is what makes the experience uniform across engines, formats and clouds, instead of one vendor deciding who can read what.
Your data stays in open formats in your own buckets, readable by any engine you point at it.

Explore Platform Details

Kubernetes Already Won

Run it in your cloud. Not theirs.

Powered by Quanton™: 5x faster, 75% lower cost

5x faster than open-source Spark, and as fast or faster than Databricks Photon on real ETL. No per-cluster premium.

Repoint your existing jobs. No rewrites. Prove it first with the free Cost Analyzer for Apache Spark.

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Real-Time Ingestion at Any Scale

OneFlow ingests database CDC, event streams and cloud storage in near real-time, and handles 350+ TB/day for our largest users.

Fully managed. No Kafka or Debezium cluster to run.

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Write Once. Query Everywhere.

Apache Hudi, Iceberg and Delta in every direction. Every catalog at once.

OneSync maintains tables and permissions across Glue, Unity, Snowflake and Hive at once, so no single catalog owns your data.

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Sub-Second Queries, Straight From the Lake

Lakegres answers interactive queries in under a second on open tables. 2-10x faster than AWS Athena in production.

A Postgres endpoint for any SQL tool, BI client or AI agent to directly query cloud storage.

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A K8s Runtime Built for Data Workloads

Virtual clusters with queues, isolation and mixed instance types, on your own Kubernetes.

Reschedules when data falls behind, absorbs shuffle failures, merges only what changed.

The Spark AI agent cuts time-to-root-cause by 80%.

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Move One Workload. Then Move the Rest.

Slash Spark and SQL ETL Costs by 75%

Run your existing Spark and SQL pipelines on Quanton™ — 5x faster than open-source Spark, and as fast or faster than Databricks Photon on real ETL, with no per-cluster premium. No rewrites required: just point your jobs to Onehouse and start saving.

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Accelerate Data Ingestion

Battle-hardened performance for near-real-time ingestion from any databases, event streams, and cloud storage. Handles 350+ TB/day for our largest users.

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Optimize Lakehouse Tables

Accelerate queries up to 30x with automated table maintenance services for Apache Hudi, Apache Iceberg, and Delta Lake. Use performance profiles to balance write vs. query cost/performance.

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Fast Data Prep for your Warehouse

Cut data warehouse costs by 30-80%. Offload compute-intensive transformations to Onehouse Compute Runtime. Share your data between platforms such as Databricks, Google BigQuery, and Amazon Redshift.

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Managed Apache Hudi at Scale

Automated table optimization on a high-performance runtime to cut compute costs on any Spark/Hudi pipeline. Built and maintained by the team that created Apache Hudi, and backed by 24/7 enterprise support.

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Vector Embeddings for Gen AI

Generate vectors from your data, stored directly in your data lakehouse for cost-efficient serving and reduced API calls.

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Trusted by Innovators

“The data lakehouse architecture now powers our data analytics and data science use cases, so we can build the next generation of data products.”

Ronak Shah

Head of Data at Apna

Full Case Study

“With automated scaling and resources that adapt to our workloads, Onehouse helps us build out our core platform differentiators rather than having to continuously optimize our data stack.”

Emil Emilov

Conductor’s Principal Software Engineer

Full Case Study

“Onehouse has allowed us to manage large volumes of data more effectively than ever, ensuring high performance and cost efficiency across the board.”

Jonathan Sims

VP, Data & Analytics at NOW Insurance

Full Case Study

“With Onehouse, we can now leverage machine learning models to gain rapid insights into outages and meter telemetry, enhancing our operational efficiency.”

Taieb Lamine Ben Cheikh

Ph.D., Data scientist, Olameter Inc.

Full Case Study

Open Data Infrastructure in Your Own Cloud Account

Full interoperability. No lock-in.

5x more scale per dollar.

Runs on your Kubernetes.

From the team that built planet-scale data infrastructure at Uber, LinkedIn and Confluent.

Ingest, Transform, Serve. One Platform.

Run it in your cloud. Not theirs.

Powered by Quanton™: 5x faster, 75% lower cost

Real-Time Ingestion at Any Scale

Write Once. Query Everywhere.

Sub-Second Queries, Straight From the Lake

A K8s Runtime Built for Data Workloads

Move One Workload. Then Move the Rest.

Slash Spark and SQL ETL Costs by 75%

Accelerate Data Ingestion

Optimize Lakehouse Tables

Fast Data Prep for your Warehouse

Managed Apache Hudi at Scale

Vector Embeddings for Gen AI

Trusted by Innovators

Don't take our word for it.