shouldiuse.io

VERDICT

Should I use Celery - Distributed Task Queue?

Not disclosed - docs.celeryq.dev

Worth it. Python teams moving real async or scheduled workload volume should use it — it's free, mature, and feature-rich. Non-Python stacks and low-volume background-job needs should look elsewhere.

Confidence

Medium. Based on 20+ public sources; review depth is thin — no numeric ratings found, so confidence is medium.

Ratings

  • Value for money
  • Ease of use
  • Feature depth
  • Support qualityCommunity-only; no paid support evidence found
  • Security posture

Pricing

$0

Open Source

ModelNot disclosed
Monthly feesNot disclosed
HardwareNot disclosed
Free tierYes

Best for

  • High-volume Python async workloads
  • Scheduled job processing
  • Teams already running Redis or RabbitMQ
  • Ops needing task routing and monitoring

Not for

  • Simple cron jobs — your OS scheduler suffices
  • Node, Go, or JVM stacks — it's Python-native
  • Anyone wanting a managed, hosted queue
  • Low-volume apps where DB polling works fine

Gotchas - check before you buy

high

Stored command injection (CVE-2021-23727) affected all versions before 5.2 — stay current.

medium

Free license, real ops bill: you run brokers, workers, scaling, and monitoring yourself.

medium

Performance problems are the most common newcomer complaint; expect tuning work.

low

No paid support — project is community-funded via Open Collective.

Pros and cons

Pros

  • Free and open source; no license fees
  • Single process handles millions of tasks per minute, sub-millisecond latency
  • Easy to use and maintain; needs no configuration files
  • Task routing, result backends, rate limiting, and monitoring built in
  • Well-maintained with excellent documentation, per long-term users

Cons

  • Requires a separate broker — Redis or RabbitMQ — to operate
  • Newcomers commonly report performance issues getting started
  • Workers are long-running processes needing daemonization and ops care

Sources & method

Analyzed 9/20/2026 - 12 sources - No active exploits for v5.6.3 found; 4 vulnerabilities catalogued historically, including a pre-5.2 command-injection CVE.

official x2review x2security x3news x5
  • CVE-2021-23727 — stored command injection, Affected all Celery versions before 5.2.
  • Unsafe pickle deserialization RCE risk, Snyk documented a Python RCE vulnerability case tied to Celery.

Key stats

  • Value for money: 5/5

    Rating

  • $0

    Starting price

  • 12

    Sources

  • Analyzed

  • Value for money: 5/5. Free open source; costs are only self-hosted ops
  • Ease of use: 3/5. Easy start, no config files; tuning trips newcomers
  • Feature depth: 4/5. Routing, scheduling, result backends, rate limiting, monitoring
  • Support quality. Community-only; no paid support evidence found
  • Security posture: 3/5. Patched pre-5.2 injection CVE; 4 vulns catalogued
  • $0 Price Open source, no paid tiers found
  • Yes Free tier Entire product is free
  • Millions of tasks/min Throughput Per process, optimized settings, per docs
  • 4 Known vulnerabilities Catalogued as of v5.6.3

Pricing

Open Source

$0

  • Full task queue, scheduling, and routing
  • Community support only
  • You host brokers and workers

Security

No active exploits for v5.6.3 found; 4 vulnerabilities catalogued historically, including a pre-5.2 command-injection CVE.

  • CVE-2021-23727 — stored command injectionAffected all Celery versions before 5.2.⁷
  • Unsafe pickle deserialization RCE riskSnyk documented a Python RCE vulnerability case tied to Celery.⁸

What users say

Users praise Celery as an easy, well-documented async job queue and scheduler, though newcomers report performance struggles.

“Python Celery is a great real time, asynchronous job queue and scheduler”
G2 review
“Celery is pretty easy to work with, has excellent documentation, and is well-maintained.”
Hacker News

Companies that could

  • Gunosy12 Uses Digdag on AWS ECS instead
Full analysis

Based on 20+ public sources; review depth is thin — no numeric ratings found, so confidence is medium.

Free, battle-tested Python task queue. Powerful at scale; overkill for simple background jobs.

Methodology

Based on 20+ public sources; review depth is thin — no numeric ratings found, so confidence is medium.

Sources

  1. Celery 5.6.3 documentationdocs.celeryq.dev
    official
  2. celery/celery on GitHubgithub.com
    official
  3. Celery (software) — Wikipediaen.wikipedia.org
    news
  4. Python Celery reviews — G2g2.com
    review
  5. Celery — Hacker News discussionnews.ycombinator.com
    review
  6. The problems with (Python's) Celery — Hatchethatchet.run
    news
  7. How to Keep Celery Task Queues Secure After EOL — TuxCaretuxcare.com
    security
  8. Case study: Python RCE vulnerability in Celery — Snyksnyk.io
    security
  9. Celery Security Audit — Sherlock Forensicssherlockforensics.com
    security
  10. How to Use Celery for Distributed Task Queues — OneUptimeoneuptime.com
    news
  11. Run Celery workers with AWS Batch — AWSaws.amazon.com
    news
  12. EC2 Python batch replaced with ECS Digdag — Gunosytech.gunosy.io
    news

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