About Dremio

Set your data free with the next-generation data lake engine

Maximize the power of your data with Dremio—the data lake engine. Dremio operationalizes your data lake storage and speeds your analytics processes with a high-performance and high-efficiency query engine while also democratizing data access for data scientists and analysts via a governed self-service layer. The result is fast, easy data analytics for data consumers at the lowest cost per query for IT and data lake owners.

Accelerate Time to Insight

Only Dremio delivers secure, self-service data access and lightning-fast queries directly on your AWS, Azure or private cloud data lake storage. The industry’s only vertically integrated semantic layer and Apache Arrow-based SQL engine reduce time to analytics insight while increasing data team productivity and lowering infrastructure costs.


cubes, extracts or aggregation tables


faster ad hoc queries and 1,700x faster BI queries


less compute spend than other SQL engines


lock-in, data copies or movement

Twingo & Dremio

Twingo is a local partner and an official representative of DREMIO in Israel.

Rethink Your Data Architecture

Dremio is shattering a 30-year-old paradigm that holds virtually every company back—the belief that, in order to query and analyze data, data teams need to extract and load it into a costly, proprietary data warehouse. We’re removing those limitations, accelerating time to insight and putting control in the hands of the user.


Separate data, not just storage, from your compute so you can future-proof your analytics architecture to leverage best-of-breed applications and engines today—and tomorrow.

Lightning Fast

Accelerate ad hoc queries 3,000x and BI queries 1,700x vs. SQL engines, eliminating the need for cubes, extracts or aggregation tables, or even to ETL your data into a data warehouse.


Provision new datasets with consistent KPIs and business logic in minutes, not days or weeks. And empower analysts to create their own derivative datasets, without copies.


Easily size the minimum compute you need for each workload, and only consume compute when running queries. Reduce compute infrastructure and associated costs by up to 90%.