Founded by Ex-Uber Data Architect and Apache Hudi Creator, – GlobeNewswire

MENLO PARK, Calif., Feb. 02, 2022 (GLOBE NEWSWIRE) -- Today Onehouse, the first managed lakehouse company, emerged from stealth with its cloud-native managed service based on Apache Hudi that makes data lakes easier, faster and cheaper.

Data has become the driving force of innovation across nearly every industry in the world. Yet organizations still struggle to build and maintain data architectures that can economically scale at the fast-paced growth of their data. As the size of the data and the AI and machine learning (ML) workloads increase, their costs rise exponentially and they start to outgrow their data warehouses. To scale any further they turn to a data lake where they face a whole new set of complex challenges like constantly tuning data layouts, large-scale concurrency controls, fast data ingestion, data deletions and more.

Onehouse founder Vinoth Chandar faced these very challenges as he was building one of the largest data lakes in the world at Uber. A rapidly growing Uber needed the performance of a warehouse and the scale of a data lake, in near real-time to power AI/ML driven features like predicting ETAs, recommending eats and ensuring ride safety. He created Apache Hudi to implement a new path-breaking architecture where the core warehouse and database functionality was directly added to the data lake, today known as the lakehouse. Apache Hudi brings a state-of-the-art data lakehouse to life with advanced indexes, streaming ingestion services and data clustering/optimization techniques.

Apache Hudi is now widely adopted across the industry used from startups to large enterprises including Amazon, Walmart, Disney+ Hotstar, GE Aviation, Robinhoodand TikTok to build exabyte scale data lakes in near-real-time at vastly improved price/performance. The broad adoption of Hudi has battle-tested and proven the foundational benefits of this open source project. Thousands of organizations from across the world have contributed to Hudi and the project has grown 7x in less than two years to nearly one million monthly downloads. At Uber, Hudi continues to ingest more than 500 billion records every day.

Zheng Shao and Mohammad Islam from Uber shared we started the Hudi project in 2016, and submitted it to Apache Incubator Project in 2019. Apache Hudi is now a Top-Level Project, with the majority of our Big Data on HDFS in Hudi format. This has dramatically reduced the computing capacity needs at Uber in the Cost-Efficient Open Source Big Data Platform at Uber blog: https://eng.uber.com/cost-efficient-big-data-platform/.

Even with transformative technology like Apache Hudi, building a high quality data lake requires months of investment with scarce talent without which there are high risks that data is not fresh enough or the lake is unreliable or performs poorly.

Onehouse founder and CEO Vinoth Chandar said: While a warehouse can just be used, a lakehouse still needs to be built. Having worked with many organizations on that journey for four years in the Apache Hudi community, we believe Onehouse will enable easy adoption of data lakes and future-proof the data architecture for machine learning/data science down the line.

Onehouse streamlines the adoption of the lakehouse architecture, by offering a fully-managed cloud-native service that quickly ingests, self-manages and auto-optimizes data. Instead of creating yet another vertically integrated data and query stack, it provides one interoperable and truly open data layer that accelerates workloads across all popular data lake query engines like Apache Spark, Trino, Presto and even cloud warehouses as external tables.

Leveraging unique capabilities of Apache Hudi, Onehouse opens the door for incremental data processing that is typically orders of magnitude faster than old-school batch processing. By combining a breakthrough technology and a fully-managed easy-to-use service, organizations can build data lakes in minutes, not months, realize large cost savings and still own their data in open formats, not locked into any individual vendors.

Industry Analysts on Onehouse

$8 Million in Seed FundingOnehouse raised $8 million in seed funding co-led by Greylock and Addition. Onehouse plans to use the money for its managed lakehouse product and to further the research and development on Apache Hudi.

Greylock Partner Jerry Chen said: The data lake house is the future of data lakes, providing customers the ease of use of a data warehouse with the cost and scale advantages of a data lake. Apache Hudi is already the de facto starting point for modern data lakes and today Onehouse makes data lakes easily accessible and usable by all customers.

Addition Investor Aaron Schildkrout said: Onehouse is ushering in the next generation of data infrastructure, replacing expensive data ingestion and data warehousing solutions with a single lakehouse thats dramatically less costly, faster, more open and - now - also easier to use. Onehouse is going to make broadly accessible what has to-date been a tightly held secret used by only the most advanced data teams.

Additional Resources

About OnehouseOnehouse provides a cloud-native managed lakehouse service that makes data lakes easier, faster and cheaper. Onehouse blends the ease of use of a warehouse with the scale of a data lake into a fully managed product. Engineers can build data lakes in minutes, process data in seconds and own data in open source formats, not locked away to individual vendors. Onehouse is founded by a former Uber data architect and the creator of Apache Hudi who pioneered the fundamental technology of the lakehouse. For more information, please visit https://onehouse.ai or follow @Onehousehq.

Media and Analyst Contact:Amber Rowlandamber@therowlandagency.com+1-650-814-4560

A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/aedd9404-e43b-49fb-9091-a4b0e57e7f39

See original here:
Founded by Ex-Uber Data Architect and Apache Hudi Creator, - GlobeNewswire

Related Posts

Comments are closed.