dungbeetle
DungBeetle is a lightweight distributed job server built in Go for queuing and executing large SQL read queries asynchronously. It decouples reporting workloads from application databases by routing queries to dedicated result databases, preventing database overload when many users request reports simultaneously.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | zerodha/dungbeetle |
| Owner | zerodha |
| Primary language | Go |
| License | MIT — OSI-approved |
| Stars | 1.3k |
| Forks | 174 |
| Open issues | 12 |
| Latest release | v2.0.1 (2024-04-10) |
| Last updated | 2026-05-14 |
| Source | https://github.com/zerodha/dungbeetle |
What dungbeetle is
A single-binary job scheduler supporting MySQL, PostgreSQL, and ClickHouse as source databases, with Redis/AMQP broker backends for job distribution. Results are written to ephemeral result tables in separate databases, allowing downstream queries against cached results rather than the primary database.
Get the dungbeetle source
Clone the repository and explore it locally.
git clone https://github.com/zerodha/dungbeetle.gitcd dungbeetle# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Requires setting up and maintaining at least one broker backend (Redis or AMQP) for job distribution; operational burden increases with scale.
- Result backend (MySQL or PostgreSQL) must handle ephemeral table creation and cleanup; consider TTL/retention policies and storage growth.
- SQL queries are defined in .sql files using goyesql format; versioning and testing of query changes must be integrated into deployment workflows.
- Worker instances are stateless and scalable, but broker and result database become potential bottlenecks; monitor queue depth and result DB resource usage.
- Job cancellation behavior differs by database: PostgreSQL drivers cancel mid-execution, but MySQL continues execution server-side; set `max_execution_time` for MySQL safety.
When to avoid it — and what to weigh
- Real-time query results required — If users need synchronous, immediate query results, asynchronous job queueing introduces unacceptable latency. Consider in-database materialized views or caching layers instead.
- Write-heavy workloads or OLTP transactions — DungBeetle is explicitly designed for read-only SQL jobs. It does not handle transactional writes or distributed consensus scenarios.
- Minimal operational overhead required — Deployment requires managing a broker backend (Redis/AMQP), result databases, and multiple server/worker instances. Adds operational complexity compared to single-machine solutions.
- Non-SQL data sources — Architecture is tightly coupled to SQL databases. If your workload involves NoSQL, APIs, or heterogeneous data sources, integration would require custom extensions.
License & commercial use
MIT License (Expat). Permissive OSI-approved license allowing unrestricted use, modification, and distribution, including in commercial software, with standard copyright and liability disclaimers.
MIT is a permissive open-source license with no restrictions on commercial use. However, Zerodha (the author) provides no explicit warranty or support commitments; commercial users should treat this as community-maintained software and conduct their own security and reliability review before production deployment.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Active |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Moderate |
| DEV.co fit | Good |
| Assessment confidence | High |
SQL injection risk in parameterized queries depends on proper use of placeholders (? for MySQL, $N for Postgres); review query definitions. No evidence of built-in authentication/authorization for HTTP API endpoints; should be deployed behind reverse proxy with access control. Broker backend (Redis/AMQP) should not be exposed to untrusted networks. Result database holds ephemeral query results; ensure appropriate isolation and cleanup policies.
Alternatives to consider
Apache Airflow
Full-featured orchestration platform for complex DAGs and dependencies, but significantly heavier than DungBeetle and overkill for simple SQL job queueing.
Celery (Python) / Sidekiq (Ruby)
Language-specific job queues with broader ecosystem support and more mature production tooling, but require application rewrite and don't specialize in SQL workload isolation.
Database-native solutions (materialized views, scheduled jobs)
MySQL Events or PostgreSQL pg_cron reduce operational dependencies but lack distributed queueing, scaling, and result caching capabilities.
Build on dungbeetle with DEV.co software developers
DungBeetle can prevent database overload from concurrent report requests. Contact us to evaluate if async job queueing fits your architecture.
Talk to DEV.coRelated on DEV.co
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dungbeetle FAQ
Can DungBeetle execute write operations (INSERT, UPDATE, DELETE)?
What happens if a job fails mid-execution?
Do I need a separate broker backend, or is one included?
How long are result tables retained?
Software developers & web developers for hire
DEV.co is a software development agency delivering custom software development services to companies building on open source. Our software developers and web developers design, integrate, and ship production systems — spanning web development, APIs, AI, data, and cloud. If dungbeetle is part of your open-source databases roadmap, our team can implement, customize, migrate, and maintain it.
Ready to decouple your reporting workload?
DungBeetle can prevent database overload from concurrent report requests. Contact us to evaluate if async job queueing fits your architecture.