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Apache ORC (Optimized Row Columnar) is an open-source columnar storage format for Apache Hadoop and related data processing ecosystems.

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Apache ORC is a columnar storage format designed for high-performance data processing in Apache Hadoop ecosystems.

Apache ORC (Optimized Row Columnar) is an open-source columnar storage format for Apache Hadoop and related data processing ecosystems. It was created in 2013 by engineers at Hortonworks (now part of Cloudera) and later donated to the Apache Software Foundation, where it became a top-level project in 2016. The project is not a company; it has no headquarters, employees, revenue, or funding.

It is maintained by a community of volunteer contributors and sponsored by the Apache Software Foundation. The repository on GitHub shows 766 stars, 513 forks, and 2,203 commits as of June 2026, with recent activity focused on C++ build fixes and security documentation. The project's primary output is the ORC file format specification and its Java and C++ implementations.

ORC is widely used in data lake architectures, particularly with Apache Hive, Apache Spark, and Presto. It competes with other columnar formats like Apache Parquet and Apache Avro. The project has no customer base, no notable clients, and no financial trajectory.

The research dossier provided contains no information about the Apache ORC project; instead, it contains data about two unrelated entities: Orchid Island Capital (NYSE: ORC), a real estate investment trust, and Oracle Corporation (NYSE: ORCL), a technology company. These are distinct from the Apache ORC project. The Apache ORC project has no recent news, funding rounds, acquisitions, layoffs, or leadership changes to report.

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Who buys this

  • Data engineers using Apache Hive for batch processing
  • Data scientists and analysts using Apache Spark for large-scale analytics
  • Organizations building data lakes on Hadoop or cloud object storage
  • Users of Presto or Trino for interactive SQL queries on columnar data

Strengths and what to watch

Strengths

  • ORC files are typically smaller and faster to read than equivalent Parquet files in Hive workloads due to better compression and predicate pushdown.
  • The format supports ACID transactions and schema evolution, making it suitable for streaming and batch ingestion pipelines.
  • The project is mature (over a decade old) and has a stable, well-documented specification with both Java and C++ implementations.

Watch for

  • ORC's adoption is heavily tied to the Hive ecosystem; as organizations migrate to Spark and Iceberg, Parquet has gained more mindshare.
  • The project has no dedicated corporate sponsor; maintenance depends entirely on volunteer contributions, which can slow bug fixes and feature development.
  • ORC's C++ implementation has had recent security fixes (e.g., bounds checking for LZO decompression), indicating ongoing maintenance needs.

Key Information

Industry
Formats
Founded
2013

Frequently Asked Questions

What is Apache ORC and what is it used for?

Apache ORC is an open-source columnar storage format designed for high-performance data processing in Hadoop ecosystems. It was created in 2013 by Hortonworks engineers and is widely used with Hive, Spark, and Presto for efficient data lake storage.

How does ORC compare to Parquet for data storage?

ORC files are typically smaller and faster to read than Parquet in Hive workloads due to better compression and predicate pushdown. However, Parquet has gained more mindshare as organizations migrate to Spark and Iceberg, making it a strong competitor.

What are the key features of the ORC file format?

ORC supports ACID transactions and schema evolution, making it suitable for streaming and batch ingestion pipelines. It also offers efficient compression and predicate pushdown, which reduces storage size and speeds up queries in data lake architectures.

Who maintains the Apache ORC project?

Apache ORC is maintained by a community of volunteer contributors and sponsored by the Apache Software Foundation. It has no dedicated corporate sponsor, so maintenance depends entirely on volunteer efforts, which can slow bug fixes and feature development.

What are the main use cases for Apache ORC?

ORC is used by data engineers for batch processing with Hive, data scientists for large-scale analytics with Spark, and organizations building data lakes on Hadoop or cloud object storage. It also supports interactive SQL queries via Presto or Trino.

Is Apache ORC still actively maintained in 2026?

Yes, as of June 2026, the ORC GitHub repository shows recent activity including C++ build fixes and security documentation updates. However, the project has no dedicated corporate sponsor, so maintenance relies on volunteer contributions, which can be slower.

Sources

  1. github.com — Project repository, commit history, and community activity as of June 2026.
  2. fullratio.com — Financial data for Orchid Island Capital (NYSE: ORC), not the Apache ORC project.
  3. investor.oracle.com — Financial results for Oracle Corporation (NYSE: ORCL), not the Apache ORC project.
  4. public.com — Earnings data for Orchid Island Capital (NYSE: ORC), not the Apache ORC project.