Onehouse
Claim this toolThe universal data lakehouse platform for accelerated, cost-effective data ingestion and processing.
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67 reviews trackedThe Bottom Line
- Price
- Paid plans only. Compare plans
Key facts
- Accelerates data ingestion and ETL pipelines by 2-10x while reducing costs by 50% or more.
- Supports all major open table formats (Hudi, Iceberg, Delta Lake) with seamless interoperability.
- Provides a fully managed, serverless platform for data processing, eliminating operational overhead.
Pros
- Significantly reduces Spark and SQL pipeline costs (50%+)
- Offers substantial performance improvements for ETL and queries (2-30x faster)
- Provides full interoperability with major open table formats, preventing vendor lock-in
- Simplifies data operations with a fully managed, serverless platform
- Supports real-time data ingestion from diverse sources (CDC, Kafka, cloud storage)
Cons
- Specific pricing details are not publicly available, requiring contact with sales.
- Azure support is listed as 'coming soon', indicating potential limitations for Azure-centric users currently.
What is Onehouse?
Onehouse is a universal data lakehouse platform designed to streamline and optimize data operations across various cloud environments. Built by the creators of Hudi and XTable, it aims to provide a single, unified data lakehouse underpinning all cloud data platforms. The platform leverages its proprietary Quanton™ engine to deliver significant performance improvements and cost reductions for SQL and Spark-based ETL pipelines, often achieving 2-3x faster processing at half the cost.
Onehouse offers a fully managed experience for data ingestion (OneFlow), supporting real-time CDC, event streams, and cloud storage files into open table formats like Apache Hudi, Iceberg, and Delta Lake. It also provides a high-performance compute runtime (Quanton Engine) for running existing SQL and Spark jobs without rewrites, featuring serverless Spark, adaptive workload optimization, and high-performance I/O. The platform emphasizes openness and interoperability, allowing users to query data anywhere with various engines and integrate across multiple catalogs, making it suitable for data engineers, data scientists, and analytics teams looking to build efficient, scalable, and cost-effective data platforms.
Available on: Web
Ratings Across the Web
4.3(67 reviews)
Onehouse holds an aggregate rating of 4.3 out of 5 from 67 reviews across SourceForge, last checked March 19, 2026.
Ratings aggregated from independent review platforms. Learn more
Preview
Key Features
- Quanton™ Engine for 2-3x faster SQL/Spark jobs at 1/2 the cost
- Incremental ELT/ETL for reduced pipeline costs
- Smart table optimizations to minimize data scanned during queries
- Consolidates and manages data in open formats to reduce cloud storage costs
- Near real-time ingestion for CDC workloads
- Zero-ops managed ELT experience with adaptive scaling
- Omnidirectional support for Apache Hudi, Apache Iceberg, and Delta Lake formats
- Seamless switching between formats and engines without data migration
Pricing
Paid
Onehouse offers paid plans. Visit their website for current pricing details.
Reviews
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4.3/5
Across 67 verified user reviews on SourceForge
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Onehouse FAQ
How does Onehouse accelerate data ingestion and processing?
Onehouse accelerates data operations by leveraging its proprietary Quanton™ engine, which delivers significant performance improvements for SQL and Spark-based ETL pipelines. This engine enables 2-3x faster processing while also reducing costs by half. It also supports real-time CDC, event streams, and cloud storage files for efficient data ingestion.
Which teams benefit most from using Onehouse?
Data engineers, data scientists, and analytics teams can significantly benefit from Onehouse. It is designed for those looking to build efficient, scalable, and cost-effective data platforms by streamlining data operations and providing high-performance compute capabilities.
How is Onehouse priced?
Onehouse is a paid product and does not include a permanently free tier. Specific pricing details are not publicly available and require direct contact with their sales team.
Can Onehouse integrate with existing data ecosystems?
Yes, Onehouse emphasizes openness and interoperability, allowing users to query data anywhere with various engines and integrate across multiple catalogs. It supports open table formats like Apache Hudi, Iceberg, and Delta Lake to prevent vendor lock-in.
What kind of data sources can Onehouse ingest?
Onehouse supports diverse data ingestion sources including real-time Change Data Capture (CDC), event streams like Kafka, and files from cloud storage. This is managed through its OneFlow feature, which ingests data into open table formats.
How does Onehouse compare to a competitor like Meltano?
Onehouse differentiates itself by offering a fully managed, serverless platform with a high-performance compute runtime (Quanton Engine) for existing SQL and Spark jobs, aiming for 2-3x faster processing at half the cost. It also provides full interoperability with major open table formats to prevent vendor lock-in.
What are the current limitations of Onehouse regarding cloud support?
Currently, Azure support for Onehouse is listed as 'coming soon'. This indicates that users primarily operating within an Azure-centric environment may find current support limited.
Source: onehouse.ai