Managed data lakehouse company Onehouse Inc. said today it has raised $35 million in a Series B funding, bringing its total funding to date to $68 million.

It also launched two new products to increase lakehouse performance and reduce cloud storage and processing costs.

The company sells a data lakehouse as a managed service based on Apache Hudi, a popular data format that Chief Executive Officer Vinoth Chandar co-created while at Uber Technologies Inc. A lakehouse is a data management architecture that combines elements of both data lakes and data warehouses, combining large amounts of structured, semistructured and unstructured data with the data management and schema enforcement features of a data warehouse.

Onehouse is focused on openness and interoperability, with support for the three leading table formats: Apache Hudi, Apache Iceberg and Delta Lake. Its particular focus is on Hudi, a data format that is admired for its speed, scalability and ability to process only data that has changed since the last computation.

The company says its platform can ingest large amounts of data at scale with sub-minute currency, transform data incrementally and automatically optimize tables for performance. It’s delivered as a managed cloud service and is also available under an open-source license.

‘Great validation’

The funding is “great validation that the product we built is resonating in the market because of how open it is and how it makes data interoperable,” Chandar said. He said the company plans to invest the new funding in research and sales.

Openness is what distinguishes Onehouse from competitors like Databricks Inc. and Snowflake Inc. “We are engine-neutral; we optimize data across Snowflake and Databricks, so you are free to use your own tools to transform data,” Chandar said. “We have a better framework for open interoperability, and we provide it with the click of a button.

The multicloud and multiengine platform integrates with all the major data catalogs. It can currently access data on Google LLC’s Cloud Platform and the Amazon Web Services Inc. cloud through multiple query engines. Support for Microsoft Corp. Azure is planned for later this year.

“Our roadmap includes cross-cloud replication,” Chandar said. “In a lot of scenarios we can be more efficient replicating rather than copying files around.”

Free monitoring

The two new products are a free cloud service called Onehouse LakeView that provides monitoring and insights to help data engineers manage and operate data lakehouse tables. LakeView provides visibility into table statistics and trends, timeline history, partition skews, file size distribution and compaction performance. It can proactively identify problems and inefficiencies and alert administrators.

Onehouse Table Optimizer is a paid managed cloud service that optimizes existing tables to accelerate data ingestion and extract/transform/load procedures for better data currency and increased performance. The service includes intelligent incremental clustering for query efficiency,  asynchronous compaction of small files and advanced storage cleaning that removes old data already committed to a table and goes beyond time-travel retention policies.

Funding was led by Craft Ventures LLC with participation by existing investors Addition and Greylock Partners LLC.

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