Introducing Conbench

Conbench is a language independent, continuous benchmarking framework, built specifically with the needs of a cross-language, platform-independent, high-performance project like Arrow in mind.

Measuring and Monitoring Arrow's Performance: Some Updated R Benchmarks

Because speed and efficiency are important design goals of Apache Arrow, we've been working on tools to help us investigate and monitor performance. Here, we introduce our R package for benchmarking and use it to revisit some previously reported CSV benchmark results.

Toward an Arrow-native world: the next stage of the Ursa journey

Announcing Ursa Computing, a startup to empower data teams and accelerate data science, machine learning, and AI work.

Chan Zuckerberg Initiative funds new Apprenticeship program to foster diversity and inclusion in Apache Arrow

In this blog post we announce the grant we have received from the Chan Zuckerberg Initiative to create an open source apprenticeship program for Apache Arrow with the objective of promoting diversity and inclusion among the maintainers.

Feather V2 with Compression Support in Apache Arrow 0.17.0

In this blog post we introduce the new Feather V2 file format and revisit file format performance benchmarks from last October.

Ultrafast pandas DataFrame loading from Apache Arrow

In this blog post, we discuss the work we've done in Apache Arrow to efficiently construct pandas DataFrame objects. In some cases, we can do it faster than pandas itself.

Ursa Labs: 2019 Highlights and 2020 Outlook

In this blog post, we take a look back at our work in 2019 and give insight into our development roadmap for 2020 and beyond.

Announcing New Ursa Labs Sponsors

We are excited to announce that Ursa Labs has several new sponsors supporting our work on Apache Arrow over the coming year:

• Bloomberg
• G-Research
• Intel
• OneSixtyTwo Technologies

Ursa Labs Team Report August to December 2019

With a busy fall full of development and some travel I wasn’t able to keep up with monthly or bi-monthly reports, so this report gives highlights about the Ursa Labs team’s work from August up until now. With 2019 nearly behind us, this also gives us a moment to reflect on everything that’s been accomplished this year and look forward to next year. We hope to write a blog post soon discussing the big picture plan ahead for 2020.

Columnar File Performance Check-in for Python and R: Parquet, Feather, and FST

In this blog post, I do some performance investigations of a few binary columnar formats (Parquet, Feather, and FST) in Python and R.