Sold by: Onehouse
Onehouse is a fully-managed open data lakehouse for analytics and AI that runs on your own Amazon EKS clusters. Ingest data from databases, event streams, and Amazon S3; transform it with Apache Spark and SQL pipelines; and serve it at sub-second latency to BI tools and AI agents, all from one copy of your data in open table formats. Run 5x more Databricks and Snowflake workloads for every dollar you already spend.
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Overview
WHY ONEHOUSE Open: Your data stays in your own Amazon S3 buckets as Apache Iceberg, Delta Lake, or Apache Hudi tables, readable by any engine and kept in sync across AWS Glue, Databricks Unity Catalog, Snowflake, and Hive Metastore. No proprietary formats, no lock-in, and nothing to export if you leave.
Fast: Quanton, the fastest lakehouse engine on the market, runs SQL and Spark ETL 5x faster than open-source Spark at up to 75% lower cost and outperforms Databricks Photon on the TPC-DS benchmark. It is fully Apache Spark compatible, so existing jobs run without rewrites. Unlocks sub-second realtime lakehouse queries with Lakegres.
Runs on any Kubernetes: Deploy in your own VPC on Amazon EKS, or on any Kubernetes cluster across clouds, on-premises, and NeoCloud providers. Your data never leaves your network, you pay only for compute, and your existing AWS discounts and commitments still apply.
WHAT YOU CAN DO WITH ONEHOUSE Ingestion: OneFlow provides managed, incremental ingestion from database change data capture (CDC), event streams, and cloud storage into analytics-ready open tables, proven at more than 350 TB per day for a single customer.
ETL and pipelines: Build transformation pipelines in SQL, Spark, Scala, or PySpark that are incremental by default and run on the Quanton engine. Table Optimizer runs compaction, clustering, cleaning, and file sizing in the background, accelerating queries up to 30x.
Serving with Lakegres: Lakegres is a Postgres-compatible serving layer that delivers low-latency queries directly on your lakehouse tables, 2-10x faster than Amazon Athena. Connect Tableau, Power BI, Looker, DBeaver, or any Postgres driver, with no data copied into a separate serving store.
Seamless access from AI agents: The Onehouse AI Gateway gives agents one governed entry point to models, tools, and data. It combines inference routing with MCP tool access, so agents like Claude Code and Codex connect once and reach Lakegres and your lakehouse tables under existing permissions. Route across providers such as OpenAI and Anthropic with failover and traffic splitting, broker credentials so agents never hold keys, and capture every trace, cost, and call in open tables you own, with no per-token markup.
For a proof of concept, qualified trial, or a private offer, contact gtm@onehouse.ai .
Highlights
- Onehouse AI Gateway
- Quanton
- Lakegres
Details
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Delivery method
Deployed on AWS
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Pricing
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Managed Lakehouse | Onehouse Managed Lakehouse solution. Contact gtm@onehouse.ai. | $0.00 |
Dimension | Cost/unit |
|---|---|
Onehouse Consumption Unit | $0.01 |
Dimensions summary
This contract listing offers two pricing dimensions. You buy Onehouse Consumption Units, which meter the compute-hours used to run the platform's services. Your cost scales with how much processing you consume, so heavier ingestion, transformation, and query workloads draw more units. The Managed Lakehouse solution is a separate option that requires you to contact the vendor at gtm@onehouse.ai for terms. The two dimensions are independent choices rather than ranked tiers. You commit under a contract and apply usage against it.
Top-of-mind questions for buyers
A Consumption Unit meters the compute-hours used to run the platform's services, such as ingestion, transformation, and queries. The platform charges an hourly compute cost based on the processing you consume. Heavier pipelines draw more compute-hours and therefore more units.
Consumption Units meter compute-hours of actual processing. When ingestion, transformation, or query jobs are not running, the platform uses serverless autoscaling that scales compute down, so idle periods draw fewer units. Your usage-based charges follow the compute actually consumed rather than a fixed rate.
The two dimensions are independent choices, not stacked charges. Consumption Units bill on metered compute-hours and scale with your workload. The Managed Lakehouse solution is a separate option with terms arranged through the vendor at gtm@onehouse.ai. Contact the vendor to confirm how the two apply together for your case.
www.onehouse.ai
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We offer refunds on a case-by-case basis. Please contact us at support@onehouse.ai if you believe you should be eligible.
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
Onehouse offers multiple tiers of support. Please contact gtm@onehouse.ai about detailed pricing for each tier.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
AI generated from product descriptions
Open Table Format Support
Data stored as Apache Iceberg, Delta Lake, or Apache Hudi tables in Amazon S3, readable by any engine and kept in sync across AWS Glue, Databricks Unity Catalog, Snowflake, and Hive Metastore
High-Performance Query Engine
Quanton engine executes SQL and Spark ETL 5x faster than open-source Spark with up to 75% lower cost, fully Apache Spark compatible, and outperforms Databricks Photon on TPC-DS benchmark
Low-Latency Serving Layer
Lakegres provides Postgres-compatible serving layer delivering 2-10x faster queries than Amazon Athena with support for Tableau, Power BI, Looker, and any Postgres driver
Managed Data Ingestion
OneFlow provides incremental ingestion from database CDC, event streams, and cloud storage into analytics-ready open tables, supporting up to 350 TB per day ingestion rates
AI Agent Integration
Onehouse AI Gateway provides governed entry point combining inference routing with MCP tool access, credential brokering, and multi-provider routing across OpenAI and Anthropic with failover and traffic splitting capabilities
Unified Lakehouse Architecture
Fully managed lakehouse platform integrating data storage, analytics, and AI workflows on a single unified platform
Incremental Compute Engine
Real-time incremental compute capabilities enabling faster model iteration and scalable experimentation
Open Standards Support
Built on open-source technologies and industry-leading open formats with native support for data lake standards
Multi-Workload Integration
Seamless integration of batch, streaming, and interactive workloads eliminating traditional data silos
Unified Governance and Security
Centralized governance and security controls across all data and AI use cases with vendor-agnostic architecture
SQL-Based Pipeline Development
Cloud-native platform enabling pipeline development, testing, and deployment using SQL without requiring complex code, with automated orchestration and scheduling.
Iceberg Lakehouse Integration
Native support for continuous ingestion and transformation of streaming and batch data to Iceberg lakehouse tables with automated schema evolution and file system optimization.
Adaptive Query Optimization
Adaptive Iceberg Optimizer that profiles data files and write patterns to automatically optimize query performance and reduce storage costs through intelligent file optimization techniques.
Multi-Source Data Connectivity
Support for connecting and replicating data from multiple streaming, file, and database sources including PostgreSQL, SQLServer, and Kinesis to Iceberg or warehouse tables.
Data Observability and Monitoring
Built-in task monitoring and data observability capabilities for detecting operational and data-related issues including volume changes, data value drift, and schema evolution.
Standard contract
No
Customer reviews
Ali M.
Personal information is properly encrypted
Reviewed on Oct 19, 2024
Review provided by G2
What do you like best about the product?
Onehouse has been helpful for us managing data lake on cloud, for our case it has been a great tool. It has the advantage of simplifying storage, sorting, and searching data that the professionals involved in data analysis require in their work.
What do you dislike about the product?
Onehouse however does not offer easily retrievable information on such integration. Much time and effort is spent trying to locate information regarding supported tools or functionalities, mostly from web searches, or calls to the IT helpdesk.
What problems is the product solving and how is that benefiting you?
Onehouse simplifies managing data lakes in the cloud environment to a single house. It also proved useful in creating a unified place for data storage and retrieval and how this information can be effectively parsed through our workforce.
Mahesh B.
Onehouse - A secured data lake to use in cloud
Reviewed on Jul 23, 2024
Review provided by G2
What do you like best about the product?
It has a user-friendly interface
It helps in data management, analytics, and reporting
We can integrate this with various tools
It solves the scalability issues and also it is cost-effective.
It helps in data management, analytics, and reporting
We can integrate this with various tools
It solves the scalability issues and also it is cost-effective.
What do you dislike about the product?
The setup process is complex and time-consuming
There is a support delay
We have to pay more for advanced features
There is a support delay
We have to pay more for advanced features
What problems is the product solving and how is that benefiting you?
The data is centralized. Means we can have all the teams or departments or applications data in one platform
Reporting and analysis is another big problem solved by Onehouse
Reporting and analysis is another big problem solved by Onehouse
Market Research
Exploring the Enigmatic: A Deep Dive into Onehouse
Reviewed on May 29, 2024
Review provided by G2
What do you like best about the product?
Ease of Implementation, Ease of Use, Number of Features
What do you dislike about the product?
There is nothing to dislike. Everything is good.
What problems is the product solving and how is that benefiting you?
It helps to provide insight from the large database in a minute, also supports all query engines and provides real-time analytics.