What Onehouse does

Onehouse operates a managed cloud data lakehouse service built on open table formats, founded in 2021 by Vinoth Chandar, the creator of Apache Hudi. Headquartered in Sunnyvale/Menlo Park, California, the company targets enterprise data teams that need to ingest, transform, and serve large-scale analytical workloads without the operational burden of running open-source lakehouse infrastructure themselves. Onehouse serves more than 30 enterprise customers, including Uber, Amazon, Walmart, Disney, ByteDance, and Google Cloud.

The platform's core product is a fully managed cloud service for Apache Hudi, with native support for Apache Iceberg and Delta Lake formats. Notable technical components include: continuous ingestion from operational databases, CDC streams, and event sources; Onetable, an open-source universal translator across Hudi, Iceberg, and Delta; LakeView, a managed query service introduced in May 2024; a Table Optimizer that automates file compaction and table maintenance; and a vector embeddings generator launched in August 2024 to support GenAI and RAG workloads. The platform runs natively on AWS, Google Cloud, and Azure, and Onehouse maintains significant contribution to both Apache Hudi and Apache XTable, anchoring the company in the governance of the lakehouse open-source ecosystem. Reported operational scale reaches hundreds of billions of records processed per day through Apache Hudi.

Onehouse monetizes through a combination of subscription-based platform fees and usage-based pricing tied to data volume and compute consumption. Its go-to-market is enterprise-led, with strategic engagements such as the close partnership with Uber (a major Hudi user) and deployments across transportation, retail, entertainment, technology, and media verticals. The company has raised $68 million in total funding across a February 2022 seed round ($8M), a February 2023 Series A ($25M), and a June 2024 Series B ($35M), with Greylock, Addition, and 8VC among the principal investors. Onehouse employed approximately 69 people as of late 2025 and operates an engineering presence in Bengaluru, India.

Name

Onehouse

Legal name

Onehouse

Website

https://onehouse.ai

Company type

Private

Founded year

2021

Operating status

Operating

Headcount range

51–100 employees

Short description

Onehouse is a managed cloud data lakehouse platform built on Apache Hudi that serves enterprise data teams. It ingests, transforms, and serves data on open table formats (Hudi, Iceberg, Delta) and offers Onetable, LakeView, Table Optimizer, and a vector embeddings generator for GenAI workloads.

Ownership category

akta.pro rank

Product category

Cloud Data Lakehouse Platform

NAICS

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518), Computer Facilities Management Services (541513), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518210)

SIC

Services-Computer Integrated Systems Design (7373), Services-Computer Programming, Data Processing, Etc. (7370)

akta.pro primary industry

Lakehouse Platforms (HDAEABAB)

akta.pro secondary industries

Data Warehouse/Lakehouse Performance Optimization & Cost Management (HDAEABAL), Cloud Operations Outsourcing (Cloud Managed Operations) (BPAEAMAC), Cloud Managed Services (M365/Azure/AWS/GCP) (BPAEABAE)

Keywords

• Data lakehouse platform
• Managed data infrastructure
• Open table formats
• Cloud data engineering
• Apache Spark engine

Headquarters

HQ city

Sunnyvale

HQ country

United States

HQ region

North America

Offices3 records

Markets served

GTM type

B2B

Offering type

Software

Cost components

Technology or R&D, Personnel, Infrastructure, Marketing or Sales, Operations

Revenue model

1. Managed Data Lakehouse Platform: Subscription-based managed service providing fully managed operations, automated performance tuning, real-time monitoring, and data governance for data lakehouse infrastructure. Customers pay for the platform deployed in their own VPC with features they choose.
2. Onehouse Compute Runtime: Serverless Spark compute with elastic scaling and cost-optimized spot instances, charged based on compute usage for processing workloads.
3. Enterprise Support: 24/7 enterprise support bundled with managed Hudi services for organizations requiring dedicated support.

Pricing tiers

Go-to-market motion2 records

Distribution channels3 records

Marketing channels6 records

Core offering

Onehouse provides a fully managed, cloud-native Universal Data Lakehouse platform built on Apache Hudi that delivers high-performance SQL and Spark-based ETL, automated table optimization across Hudi, Iceberg, and Delta Lake formats, near real-time managed data ingestion, and multi-catalog synchronization. It is sold as a subscription-based managed service deployed in customer VPCs across AWS, GCP, and Azure, complemented by free self-serve tools (LakeView, Cost Analyzer for Apache Spark) and a self-managed Kubernetes operator option.

Product overview

Onehouse is a Universal Data Lakehouse platform offering a modular architecture built around its core Quanton Engine. The platform consists of core products (Quanton Engine, Table Optimizer, LakeBase, Open Engines, OneFlow, OneSync) that work together to provide end-to-end lakehouse capabilities from data ingestion through query optimization. Deployment options include Onehouse Cloud (fully managed multi-cloud) and the Quanton K8s Operator (self-managed Kubernetes). The platform supports all major open table formats (Apache Hudi, Apache Iceberg, Delta Lake) via Apache XTable interoperability. Free tools (LakeView, Cost Analyzer) are available for monitoring, while the company contributes to open source projects Apache Hudi and Apache XTable.

Differentiator

Problem solved

Functional benefit

Brands

• Onehouse Cloud: Fully managed lakehouse platform deployed in customer's VPC
• Quanton Engine
• LakeBase
• OneFlow
• Onehouse LakeView
• Table Optimizer
• Open Engines
• OneSync
• Quanton K8s Operator

Products and services

• Quanton Engine High-performance SQL and Apache Spark engine that delivers 2–3x price/performance gains on ETL pipelines, with intelligent workload optimization, serverless Spark, elastic scaling, and vectorized lakehouse I/O. Designed for enterprise data engineering teams running large Spark workloads.
• Table Optimizer Automated table maintenance service for Apache Hudi, Apache Iceberg, and Delta Lake that accelerates queries 2–30x by tuning compaction and performance profiles. Used by data platform teams to keep lakehouse tables performant without manual tuning.
• LakeBase Interactive SQL query service for the lakehouse that delivers low-latency queries directly on lakehouse tables. Targeted at analysts and applications needing fast SQL access without moving data into a separate warehouse.
• Open Engines Managed clusters for open-source compute engines including Trino, Ray, and Apache Flink. Enables stream processing, BI, and AI workloads on the same lakehouse data. Aimed at platform teams that want managed open-source query and compute.
• OneFlow Data Ingestion Fully managed ELT ingestion service for databases, event streams, and cloud storage with near real-time CDC support and adaptive scaling. Built for data engineering teams that need fast, efficient ingestion into the lakehouse.
• OneSync Multi-catalog synchronization service that syncs a single copy of lakehouse data to every query engine, supporting simultaneous sync with Snowflake, Databricks, BigQuery, and others. Targeted at organizations that need a single source of truth across multiple engines.
• Onehouse Cloud Fully managed Onehouse Platform deployment that runs in a customer's own VPC on any cloud (AWS, GCP, Azure) with automated operations, performance tuning, real-time monitoring, and data governance. Sold as an annual subscription to enterprise customers.
• Quanton K8s Operator Kubernetes operator that brings Quanton's performance gains (approximately 4x) to self-managed Kubernetes environments, enabling faster Apache Spark jobs on existing K8s infrastructure. Sold to platform teams that prefer to operate their own Kubernetes.
• LakeView Free tool for monitoring and analyzing lakehouse performance and costs. Used by data platform teams for lakehouse observability.
• Cost Analyzer for Apache Spark Free tool that identifies hidden compute waste in Apache Spark workloads and helps cut Spark spend by 60%+. Used by data engineering teams to surface savings opportunities before adopting the paid managed platform.

Quantifiable outcome

• 80% cost reduction (from ~$1.16M to ~$200K annually)
• +6 more outcomes

Named customers13 records

Segments3 records

Ideal customer profiles2 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

Integration9 records

AI capability4 records

Feature6 records

Partnerships

Two partnerships are on record, tiered strategic and reference.

• UberstrategicTechnology or IntegrationUber created Apache Hudi in 2015 and operates one of the world's largest data lakes powered by Hudi (19,500 datasets, 6 trillion rows/day, 350 PB storage). Uber is now engaging with Onehouse to upgrade to Hudi 1.x and contribute internal customizations back to open source.
• NOW InsurancereferenceOthersMay 2024 deployment by NOW Insurance achieved 100x performance improvements and 50% reduction in Airflow operating costs. Referenced in market research as a notable implementation case.

Scale indicators9 records

Recent moves6 records

Expansion highlights8 records

Others

• Confluent: Confluent is the leading managed streaming platform (Apache Kafka) and an adjacent data infrastructure peer. Onehouse's OneFlow ingestion and Flink integration overlap with Confluent's data pipeline story for real-time lakehouse ingestion.

Broad incumbents

• Cloudera: Cloudera provides hybrid and multi-cloud data platforms with Iceberg/Hudi support and enterprise governance. It is a broader incumbent selling to similar large enterprise data customers and competes on private-cloud lakehouse deployments.
• Snowflake: Snowflake is the dominant cloud data warehouse and is expanding into lakehouse (Iceberg Tables, Polaris catalog) and AI workloads. It is both a competitor (warehouse spend) and a target integration for Onehouse via OneSync, depending on customer architecture.
• Microsoft (Fabric/OneLake/Synapse): Microsoft Fabric unifies OneLake, Synapse, and Power BI into a single lakehouse-oriented platform, directly contesting Onehouse's value proposition on Azure. Enterprise standardization on Microsoft could foreclose deals.
• Amazon Web Services (Glue/Athena/EMR/Lake Formation): AWS offers a suite of native lakehouse-adjacent services — Glue (catalog/ETL), Athena (query), EMR (Spark), and Lake Formation (governance). It is the largest incumbent Onehouse must displace or sit alongside in enterprise deals.
• Google Cloud (BigQuery/BigLake/Dataproc): Google's BigQuery with BigLake and Dataproc provides managed lakehouse capabilities on GCP, one of Onehouse's three deployment clouds. Google is both a customer (referenced in Onehouse's logo list) and a competitive platform.

Direct peers

• Starburst: Starburst provides managed Trino (formerly PrestoSQL) for federated querying across data lakes and warehouses. It overlaps with Onehouse's Open Engines and OneSync offerings, targeting the same multi-engine, multi-format analytics buyer.
• Databricks: Databricks is the largest unified data and AI platform built around the Delta Lake table format. It is the most direct competitor to Onehouse's lakehouse thesis, with a much larger product surface (compute, governance, ML, GenAI) and significantly greater scale.
• Dremio: Dremio offers an open lakehouse platform with strong Apache Iceberg support and SQL query performance. Like Onehouse, it positions itself as an open, engine-agnostic alternative to proprietary warehouses, and competes head-on in enterprise lakehouse deployments.

Emerging players

• Apache Iceberg (project / Tabular): Apache Iceberg is the primary open table format competing with Hudi, with Tabular (founded by Iceberg creators, acquired by Databricks) having been the most prominent commercial entity. Onehouse's multi-format strategy means it partners with and competes against Iceberg-aligned tooling and managed services.

Market position

Strengths4 records

Weaknesses4 records

Competitive moat5 records

Key risks5 records

Key highlights7 records

Customer concentration

• Xx.com/Onehousehq
• LinkedInlinkedin.com/company/onehousehq

Revenue estimate

Valuation estimate

Number of profiles

Profiles2 records

Funding overview

Funding rounds3 records

Investors4 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Onehouse