HTCondor
HTCondor: A free, self-hosted scheduler for distributed serial and parallel compute jobs. Ranked #17 of 25 in Job Scheduler Software by our editors (7.4/10); pricing: Free plan; best for free distributed batch computing.
At a glance
- Editor score7.4 / 10
- PricingFree plan
- Best forFree distributed batch computing
- Free planYes
- Paid fromFree
- Dependency controlsYes
- Facts checked20 Sep 2026
Where it wins
- Free and open source under the Apache License 2.0
- Supports queueing, resource matching, dependencies, retries, and recovery
- Runs across clusters, cloud resources, grids, Windows, macOS, and Linux
Where it doesn't
- Self-hosted deployment requires your team to operate the environment
- Focused on compute-intensive workloads rather than general-purpose scheduling
- Concurrent-job limits depend on the configured pool, not a product plan
Our verdict on HTCondor
HTCondor is an open-source workload management system for compute-intensive serial and parallel jobs. It is designed for academic, government, and commercial organizations that need to queue work, select execution machines, monitor progress, and report completion. The system can manage dedicated clusters, idle desktop workstations, cloud resources, and grid environments, making it a fit for teams running distributed batch workloads across varied compute resources.
There is no paid plan structure to compare: HTCondor is free and distributed under the Apache License 2.0. Its operating model is self-hosted, and concurrent-job limits depend on the configured pool rather than a product plan. That makes it suitable for teams that want control over their scheduling environment and can operate the underlying infrastructure. It is less suitable for buyers seeking a hosted scheduler with plan-based capacity or a managed operating model.
HTCondor’s main strength is the depth of its workload controls. Job queueing policies and ClassAds support resource matching, while DAGMan handles workflow dependencies and configurable retries for failed nodes. Automatic restart after execution-machine failure, checkpointing, job migration, and file transfer without a shared filesystem address common challenges in distributed execution. Job monitoring, completion reporting, and Python bindings add operational and development support. Choose HTCondor when distributed compute control, recovery, and workflow dependencies matter more than turnkey deployment or a broad named integration ecosystem.
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HTCondor pricing
HTCondor fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Deployment | Self-hosted |
| Dependency controls | Yes |
| Retry and recovery | Yes |
| Monitoring and alerts | Yes |
| Agent-based execution | Yes |
| Concurrent job limit | Not verified |
| Deployment | Self-hosted |
| Platforms | Windows, macOS, Linux |
| Support | Email, Community, Docs |
| Built for | Small business, Mid-market, Enterprise (editorial estimate) |
| Pricing | Free plan |
| Website | htcondor.org |
| Facts checked | 20 Sep 2026 |
Alternatives to HTCondor
- BMC Control-MA broad scheduler for governed enterprise automation, with a high starting price.9.4
- IBM Workload SchedulerA comprehensive scheduler for organizations coordinating complex hybrid workloads.9.2
- Slurm Workload ManagerA focused, free scheduler for self-hosted HPC and GPU workloads.9.0
See all HTCondor alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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