Bodo 2025.6 is Here: Supercharged Data Operations with Iceberg, Merge, and Sort

We are thrilled to announce the release of Bodo 2025.6, a major update focused on dramatically expanding the power and compatibility of our DataFrame library. This release brings some of the most requested and powerful data manipulation features to the Bodo DataFrame library, enabling you to do more with your data, faster than ever.

Highlights of Bodo 2025.6

Read Apache Iceberg Tables Natively

The headline feature of this release is native support for reading Iceberg tables with pd.read_iceberg. Our implementation is built for performance, with critical optimizations like projection, filter, and limit pushdown to minimize data movement. It also includes powerful features like time travel, allowing you to query historical versions of your data effortlessly.

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Core DataFrame Operations Unlocked

We're excited to introduce initial support for two fundamental DataFrame operations:

• merge(): You can now perform inner joins on your DataFrames, a cornerstone of data analysis and preparation workflows.
• sort_values(): Efficiently sort your data at scale, a critical step for analysis, reporting, and downstream processing.

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Massive Expansion of the Bodo API

This release adds over 80 new methods to our Series API, significantly improving compatibility and making it easier than ever to scale your existing Pandas code. Key additions include:

• 46 Series.str methods for advanced string manipulation (e.g., str.find(), str.partition()).
• 30 Series.dt accessors for sophisticated date/time handling (e.g., dt.dayofweek, dt.is_month_start).
• 7 core Series methods including the highly-requested isin() and clip().

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Performance and Power Boosts

Beyond new features, we've enhanced the core engine. You'll see improved support for arbitrarily complex filter expressions in both DataFrame and Series, giving you more flexibility in your queries. We've also substantially improved the performance of many computations and significantly sped up head() calls for quicker data previews.

Finally, we have laid the foundational infrastructure for groupby operations, with full support coming in our next release!

Go ahead, pip install bodo and test drive it!

Also be sure to visit our GitHub repository for more information and join the conversation in our community Slack.