About Onehouse

Onehouse is a fully managed cloud-native lakehouse service that ingests data from various sources in near real-time, enabling organizations to maintain a single source of truth without the need for complex data replication. By leveraging Apache Hudi and supporting multiple query engines, it reduces operational costs by over 50% while providing scalable access to analytics-ready data.

```xml <problem> Organizations struggle to maintain a unified data repository due to the complexities of ingesting data from diverse sources and the need for costly data replication across data warehouses and data lakes. Traditional ETL processes are often slow and expensive, hindering real-time analytics and efficient data processing. </problem> <solution> Onehouse provides a fully managed, cloud-native data lakehouse service that simplifies data ingestion from various sources, enabling organizations to maintain a single source of truth. By leveraging Apache Hudi and XTable, Onehouse supports multiple query engines and use cases, including BI, real-time analytics, and AI/ML. The platform eliminates the need for complex data replication, reduces operational costs, and provides scalable access to analytics-ready data. Onehouse offers automagic file sizing, partitioning, clustering, catalog syncing, indexing, and caching. </solution> <features> - Fully managed pipelines for database CDC and streaming ingestion with minute-level data freshness - Support for Apache Hudi, Apache Iceberg, and Delta Lake table formats via XTable for interoperability across catalogs and query engines - Low-code incremental processing capabilities for optimized ELT/ETL costs - Data validation and quarantine features to ensure data quality - Compatibility with query engines like Snowflake, Databricks, Redshift, BigQuery, EMR, Spark, Presto, and Trino - Secure architecture with SOC2 Type 2 and PCI DSS compliance, SSO integration, access controls, and standard encryption </features> <target_audience> Onehouse targets organizations seeking to unify their data, reduce ETL costs, and enable real-time analytics, including data engineers, data scientists, and data analysts across various industries. </target_audience> ```

What does Onehouse do?

Where is Onehouse located?

Onehouse is based in Menlo Park, United States.

When was Onehouse founded?

Onehouse was founded in 2021.

How much funding has Onehouse raised?

Onehouse has raised 68000000.

Location

Menlo Park, United States

Founded

2021

Funding

68000000

Employees

74 employees

Major Investors

Craft Ventures

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Onehouse

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Executive Summary

onehouse.ai 7K+

Crunchbase

Founded 2021 – Menlo Park, United States

Funding

Estimated Funding

$50M+

Major Investors

Craft Ventures

Team (50+)

No team information available.

Company Description

Problem

Organizations struggle to maintain a unified data repository due to the complexities of ingesting data from diverse sources and the need for costly data replication across data warehouses and data lakes. Traditional ETL processes are often slow and expensive, hindering real-time analytics and efficient data processing.

Solution

Onehouse provides a fully managed, cloud-native data lakehouse service that simplifies data ingestion from various sources, enabling organizations to maintain a single source of truth. By leveraging Apache Hudi and XTable, Onehouse supports multiple query engines and use cases, including BI, real-time analytics, and AI/ML. The platform eliminates the need for complex data replication, reduces operational costs, and provides scalable access to analytics-ready data. Onehouse offers automagic file sizing, partitioning, clustering, catalog syncing, indexing, and caching.

Features

Fully managed pipelines for database CDC and streaming ingestion with minute-level data freshness

Support for Apache Hudi, Apache Iceberg, and Delta Lake table formats via XTable for interoperability across catalogs and query engines

Low-code incremental processing capabilities for optimized ELT/ETL costs

Data validation and quarantine features to ensure data quality

Compatibility with query engines like Snowflake, Databricks, Redshift, BigQuery, EMR, Spark, Presto, and Trino

Secure architecture with SOC2 Type 2 and PCI DSS compliance, SSO integration, access controls, and standard encryption

Target Audience

Onehouse targets organizations seeking to unify their data, reduce ETL costs, and enable real-time analytics, including data engineers, data scientists, and data analysts across various industries.