facebookincubator/velox

A composable and fully extensible C++ execution engine library for data management systems.

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Summary Information

Updated 5 minutes ago
Added to GitGenius on September 16th, 2026
Created on July 23rd, 2021
Open Issues & Pull Requests: 1,584 (-2)
GitHub issues: Enabled
Number of forks: 1,610
Total Stargazers: 4,212 (+0)
Total Subscribers: 112 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 0.6 hours
Mean response time: 22.1 days
90th percentile: 34.8 days
Tracked items: 934

Most active contributors

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How this project is maintained

Roughly one issue in three opened in the past year never receives a reply. 74% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 70% of tracked open issues have had no activity in three months, so the open count overstates what is actively being worked. Only 39% of issues opened in the past year have been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 650
New in 7 days: 6
Closed in 7 days: 3
Avg open age: 393 days
Stale 30+ days: 611
Stale 90+ days: 539

Recent activity

Opened in 7 days: 6
Closed in 7 days: 3
Comments in 7 days: 0
Events in 7 days: 6

Top labels

  • bug (536)
  • enhancement (450)
  • triage (448)
  • fuzzer-found (171)
  • build (168)
  • fuzzer (111)
  • flaky-test (28)
  • good first issue (26)

Detailed Description

Velox is a composable and fully extensible C++ execution engine library for data management systems.

The project addresses the need for a reusable, high-performance execution layer that can be embedded in diverse data processing platforms. Rather than building query execution from scratch, systems can integrate Velox as a library to handle the computational core of data operations. The engine is designed around composability, allowing developers to mix and match components, and extensibility, enabling customization of functions, types, and operators to match specific system requirements.

Velox suits organizations building data warehouses, analytics platforms, or other systems that require sophisticated query execution but want to avoid reimplementing low-level optimization and execution logic. It is particularly valuable for teams with C++ expertise who need fine-grained control over execution behavior and performance tuning. The library provides a foundation for systems that process large datasets efficiently while maintaining the flexibility to add domain-specific operations without forking the codebase.

The project demonstrates sustained engineering effort with regular commits across its core execution engine, expression evaluation, and function libraries. Development activity shows consistent attention to performance optimization and the addition of new operators and data types. The codebase reflects a mature approach to extensibility, with clear patterns for integrating custom functionality. Contributions span multiple areas of the execution pipeline, indicating active maintenance of both foundational components and higher-level features.