Ross ROSS = Recommend OSS · open-source software intelligence for agents

OpenHFT/Chronicle-Queue

Some data may be outdated — see provenance labels.

Micro second messaging that stores everything to disk observed · 2026-09-24

github.com/OpenHFT/Chronicle-Queue · homepage · Java · Apache-2.0 (permissive) observed · 2026-09-24

Health v2 · maintenance only

94/100

  • Activity 96
  • Release rhythm 87
  • Longevity 100

Flags: no_readme

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.

  • gap_med: 9
  • age_days: 4888
  • days_rel: 85
  • days_push: 27
  • n_releases_24m: 34

Full methodology

Adoption not part of the score

3815 stars · 567 forks observed · 2026-09-24

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Chronicle Queue is a Java library providing microsecond-latency, persisted messaging that stores every message to disk in an append-only, zero-GC format. It supports deterministic replay and high-throughput inter-process communication, with an enterprise edition adding replication and cross-language support.

Use cases

  • persist millions of messages per second to disk with microsecond latency
  • build event-sourced systems with deterministic replay of all messages
  • share data between JVM processes with low-latency IPC
  • capture audit logs where every message must be durably recorded
  • eliminate GC pauses from a trading system's critical path
  • replay market data feeds for backtesting

When to choose

  • you need durable, append-only messaging with consistent single-digit microsecond latencies on the JVM
  • you require complete auditability and replay of every message
  • you're building low-latency trading or financial systems in Java
  • you need high-throughput IPC between processes without a network hop

When to avoid

  • you need a distributed broker with multi-language clients out of the box (community edition is Java-centric)
  • your throughput needs are modest and a standard message broker like Kafka or RabbitMQ suffices
  • you need flexible consumer semantics like competing consumers or per-message acknowledgments
  • your data is small-volume and a database or log file is enough

Facets

library · maturity stable

message-queue serialization logging caching fintech performance developer-tools jvm windows low-latency persisted-messaging zero-gc event-sourcing off-heap microsecond-latency messaging linux macos

3 sources

Member repositories

RepositoryRoleHealth v2
OpenHFT/Chronicle-Queuemain94

For agents

markdown · JSON · MCP: product_card(name="OpenHFT/Chronicle-Queue")

Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem