
TL;DR
Today, we're thrilled to share that Onehouse Cloud is now available in Microsoft Azure, in addition to our existing support for Amazon Web Services (AWS) and Google Cloud (GCP), making Onehouse now available on all the three largest public cloud providers in the world . Starting today, Azure users can sign up for early access to the full Onehouse platform – bringing faster, more cost-effective data lakehouse infrastructure to the Azure ecosystem.
Azure has become one of the most important platforms for enterprise data and AI workloads, with deep integration across the broader Microsoft ecosystem. Many of the largest global enterprises already run mission-critical data infrastructure on Azure, making it a natural home for modern lakehouse platforms.
Bringing Onehouse to Azure was a key milestone for us. As more organizations operate in multi-cloud and hybrid environments spanning public cloud and on-prem systems, supporting Azure ensures Onehouse can meet customers wherever their data infrastructure already lives
Over the past year, we've spoken with dozens of data teams on Azure who share a common frustration: they want faster, cheaper Apache SparkTM to power their data lakehouse on Azure, without sacrificing openness or flexibility. These teams are running complex ETL pipelines, building real-time analytics, and increasingly powering AI workloads – and they need infrastructure that keeps up with their scale without breaking the bank.
With Onehouse Cloud on Azure, we're answering that call. The full Onehouse platform is now available to Azure customers: OneFlow data ingestion, SQL and Spark jobs on the Quanton engine, lakehouse table optimization, LakeBaseTM, Open Engines and OneSyncTM.
This launch builds on a deep, existing partnership between Onehouse and Microsoft. Together, we co-created Apache XTable™ (Incubating), the open-source project that powers interoperability between Apache HudiTM, Apache IcebergTM, and Delta Lake. XTable is already a core component of Microsoft OneLake's table format virtualization, enabling OneLake to seamlessly serve Delta Lake tables as Apache Iceberg.
Bringing Onehouse Cloud to Azure is a natural next step in this collaboration, and we're excited to continue working closely with the Azure team to deliver the best possible lakehouse experience for joint customers.
Onehouse Cloud on Azure is deployed directly within your Azure VNet. Your data never leaves your environment, it stays in your Azure Data Lake Storage (ADLS) accounts, governed by your security policies and network controls. Onehouse operates as a managed service within your infrastructure, giving you the performance and ease of a fully managed platform with the security posture of a self-hosted solution.
If you're already invested in the Microsoft Fabric and Microsoft OneLake ecosystem, Onehouse gives you a powerful upgrade path for your data ingestion, table services, and Spark jobs. Your data stays in ADLS and remains registered in OneLake catalog, so downstream consumers, whether they're using Power BI, Synapse, or third-party engines, continue to access data without disruption. With OneSync, Onehouse keeps your table metadata in sync with Microsoft OneLake automatically.
If you're building a data lakehouse for the first time, Onehouse now offers the easiest and most cost-effective path to get started on Azure. Instead of stitching together ingestion frameworks, Spark clusters, and table optimization scripts, Onehouse provides a single managed platform that handles all of it with data stored openly in ADLS using Apache Hudi, Apache Iceberg, and/or Delta Lake.
Onehouse Cloud on Azure integrates natively with key Azure services:
For those new to Onehouse, here's a quick overview of what you get:

OneFlow Data Ingestion – Battle-tested, managed ingestion from databases, event streams, and cloud storage into your lakehouse. OneFlow handles schema evolution, data quality, and delivers near-real-time freshness with lag-aware scheduling.
SQL & Spark Jobs, Powered by Quanton™ – Run your existing Apache Spark and SQL ETL pipelines on Quanton, our purpose-built execution engine that delivers 3-4x better price/performance than open-source Spark and other leading Spark platforms. No rewrites required – just point your jobs to Onehouse and start saving.
LakeBase™ – A low-latency serving layer built directly on open lakehouse tables, delivering database-speed query performance for BI dashboards and AI agent workloads through a Postgres-compatible endpoint.
Table Optimizer – Accelerate query performance up to 30x across any engine with automated table maintenance for Apache Hudi, Apache Iceberg, and Delta Lake.
Open Engines – Spin up open source engines like Trino, Ray and Apache Flink™ with a single-click, pre-connected and optimized for your tables in Onehouse.
OneSync™ – Multi-catalog metadata sync that keeps your tables accessible across Microsoft OneLake, Snowflake, Databricks Unity Catalog, AWS Glue, and more from a single copy of data.
Onehouse Cloud on Azure is now available in preview. If you're an Azure user looking for faster, cheaper, and more open data lakehouse infrastructure, we'd love to hear from you.
Want to see exactly how much you could save on Apache Spark workloads? Try our Spark analysis tool to see how much you can save with Quanton, or directly get started below.
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