Company Research Report: Onehouse

Company Overview

• Name: Onehouse

• Mission: To empower enterprises to deploy and manage a world-class data lakehouse in minutes, eliminating data format, table format, compute, and catalog lock-ins while guaranteeing interoperability with virtually any warehouse/data processing engine.

• Founded: 2021

• Founders: Vinoth Chandar, the creator and PMC chair of the Apache Hudi project

• Key People:

• Vinoth Chandar – CEO & Founder

• Gaetan Castelein – CMO and Head of Sales

• Kyle Weller – Head of Product

• Varun Madan – Head of Engineering

• Tiffany Jordan – Head of Talent and Business Operations

• Nilesh Mahajan – Head of Platform

• Rajesh Mahindra – Head of Infrastructure

• Headquarters: Menlo Park, California, USA

• Number of Employees: Approximately 51-200 employees

• Revenue: No information is available

• Known For: Developing and delivering fully-managed, cloud-native lakehouse services built on Apache Hudi, offering high-performance ingestion pipelines and optimizing tables for maximum query performance. Known for eliminating lock-in and enhancing interoperability across analytics and AI use cases.

Products

Onehouse offers the following products and solutions:

1. Universal Data Lakehouse:

• Description: A fully managed cloud data lakehouse solution that supports all data sources and query engines with open data architecture.

• Key Features:

• Fully managed cloud service

• Support for Apache Hudi, Apache Iceberg, and Delta Lake

• Open data format interoperability

• High-performance ingestion and low latency

• Incremental data processing

2. LakeView:

• Description: A free lakehouse observability tool for the open source software community.

• Key Features:

• Critical insights and dashboards

• Performance diagnostics and optimization

• Data issue debugging

3. Table Optimizer:

• Description: Automates data lakehouse optimizations by managing data layout and table services.

• Key Features:

• Automated compaction, clustering, and cleaning

• Focus on reducing operational costs and improving query efficiency

4. XTable:

• Description: Provides data interoperability across Apache Hudi, Apache Iceberg, and Delta Lake.

• Key Features:

• Format flexibility and unified data access

• Compatibility across diverse data systems

5. Vector Embeddings Generator:

• Description: Manages vectors at scale, supporting generative AI and other models.

• Key Features:

• Ingestion from streams and databases

• Automated vector storage and retrieval

Recent Developments

• Funding:

• In June 2024, Onehouse raised $35M in Series B funding led by Craft Ventures, with participation from Addition and Greylock Partners.

• Product Launches:

• LakeView and Table Optimizer: Both tools were launched to enhance data lakehouse operations by offering observability and automated data optimization services.

• Vector Embeddings Generator: Launched to aid management of vectors at scale for AI applications, aimed at reducing costs associated with training AI models.

• Partnerships:

• Collaboration with industry leaders such as Google and Microsoft, contributing to the development of the Apache XTable project to solve data lakehouse interoperability challenges.

Additional Information

• Customer Impact: Known for significant customer insights and efficiency improvements, Onehouse's solutions have been leveraged by industries such as technology, finance, healthcare, and retail to enhance data freshness, AI capabilities, and operational performance.

• Core Technology: Powered by Apache Hudi, a pioneering open-source technology for building and managing scalable lakehouse environments.

No further financial specifics or additional partnerships were detailed in the provided data.