Floe is a Lakehouse SQL compute engine designed to enable robust ad-hoc SQL queries on large and complex data models. The platform aims to support business users in efficiently executing sophisticated SQL operations while ensuring results are financially auditable. Floe is positioned to address the need for scalable, concurrent, and cost-effective SQL analytics on lakehouse architectures.
The tool offers features such as workload isolation and the ability to embrace concurrency, allowing organizations to scale from a single user to thousands. Floe supports the PostgreSQL SQL dialect and provides connectivity options including DBC, Arrow, MCP, and Python. It also integrates with a range of client, business intelligence (BI), and artificial intelligence (AI) tools, facilitating a broader ecosystem for analytics and data science workflows.
According to recent updates, Floe is under active development and is expected to enter Beta soon. The platform’s development includes features like FloeScan, which enables interactive queries on massive Iceberg and Delta lakehouse tables.
Floe is developed by FloeDB, Inc. and is intended for organizations seeking scalable, auditable, and efficient SQL analytics on their lakehouse data infrastructure.
Floe sits in PulseGate's Databases (SQL, NoSQL, vector, graph) category. It enables business users to efficiently run robust, auditable SQL queries on large-scale lakehouse data. Floe is a B2B product aimed at business analysts and data engineers. Floe is available on the web.
Floe first shipped in 2025. The project is developed in the open on GitHub with 85 stars and 90 commits in the last 90 days. Key capabilities include Ad-hoc SQL queries, lakehouse architecture, and postgreSQL dialect. It exposes integrations via an MCP server and a public API. Floe is currently in beta.
Summary written by a language model from the project’s public pages.
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