Modern enterprise analytics,

from question to execution

Bodo gives teams a modern foundation for analytics in the AI era — where business users, data teams, and agents can work in the languages and tools they already know, with the trust and performance their enterprises require.

Open, scalable, and built for the future of analytics

Open and modular

Built on open source foundations under the Apache 2.0 license.

Works with your stack

Keep the languages and workflows your teams already know.

Built-in governance

Keep analytics workflows governed, validated, and under enterprise control.

Performance at scale

Accelerate analytics and AI workflows from question to execution.

Open and modular

Built on open source foundations under the Apache 2.0 license.

Works with your stack

Keep the languages and workflows your teams already know.

Built-in governance

Keep analytics workflows governed, validated, and under enterprise control.

Performance at scale

Accelerate analytics and AI workflows from question to execution.

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PyDough

The trusted answer layer for enterprise AI

The most accurate, secure, and verifiable answer layer for enterprise AI—enabling anyone to safely turn their enterprise data into trusted answers.

A semantic DSL closer to human language
Built specifically to help LLMs reason
Built-in guardrails via a semantic layer
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Bodo Engine

The high-performance execution layer for modern data and AI workloads

Bodo Engine gives data teams the performance of a distributed compute engine with the simplicity of the tools they already know. Run Pandas, Python, and SQL across CPUs and GPUs — with no data migration, no workflow changes, and no code changes.

7x

Faster than Polars multi-GPU

3x

Faster 3× than Dask-CuDF

The latest from the our engineering blog

The latest and greatest benchmarks, comparisons, use cases, and other product news from the Bodo engineering team.

How BodoSQL Uses and Extends Apache Calcite: From SQL Text to Optimized Execution Plans

We explore how BodoSQL uses Calcite, explain the role of each major component and how we customized it for our use case, and finally discuss how we keep those customizations up-to-date as the upstream project evolves. 

PyDough vs. Malloy vs. PRQL: What's the Difference?

We’ll walk through how each system: represents relationships between datasets, constructs queries from that representation, and constrains (or fails to constrain) the space of possible queries.

Fully Open Source Trustworthy Text-to-Analytics Stack for Iceberg Data with PyDough and BodoSQL

We demonstrate the first fully open source text-to-analytics stack for Apache Iceberg data in a simple workflow. This stack brings together three open source technologies: PyDough, BodoSQL, and Apache Iceberg.

How BodoSQL Uses and Extends Apache Calcite: From SQL Text to Optimized Execution Plans

We explore how BodoSQL uses Calcite, explain the role of each major component and how we customized it for our use case, and finally discuss how we keep those customizations up-to-date as the upstream project evolves. 

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Get in touch

Have questions or want a personalized demo? Just give our team a shout—we’d love to chat!