Data Access for Data Science


Apache Arrow is a cross-language development platform for in-memory data. Dremio is a data-as-a-service platform.

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It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. It also provides computational libraries and zero-copy streaming messaging and interprocess communication. Languages currently supported include C, C++, Java, JavaScript, Python, and Ruby.

Dremio makes your data easy, approachable, and interactive, no matter how many terabytes, no matter where it's stored. Dremio optimizes your data so you don't have to.

In this talk, we'll provide an overview of Dremio and Arrow, and outline how projects like Pandas are utilizing Arrow to achieve high performance data processing and interoperability across systems. We'll then show how companies can utilize Arrow to enable users to access and analyze data across disparate data sources without having to physically consolidate it into a centralized data repository. Finally, we'll discuss the 12-month roadmap of Apache Arrow, including Arrow Kernels, an exciting area of development in the Arrow community.

If you are using Apache Arrow, please help the Apache Arrow Project