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Apache YuniKorn vs HTCondor

Apache YuniKorn

yunikorn.apache.org

HTCondor

htcondor.com

Side by side

FigureApache YuniKornHTCondor
Price fromFree—
Free planYes—
Free trial——
Open source——
WebYesYes
Windows—Yes
macOS—Yes
Linux—Yes
APIYesYes
Self-hostedYesYes
Plans published10
Spec score · GPU Cluster Management Software8.1 (#6)7.9 (#8)
LicenseThe software is licensed under the Apache License 2.0.HTCondor Software Suite is licensed under Apache License, Version 2.0.
PurposeApache YuniKorn is a resource scheduler for running batch, data, and machine learning workloads on Kubernetes.HTCondor creates a High-Throughput Computing environment by using the computing power of networked machines, clusters, cloud resources, and international grids.

Plans

Apache YuniKorn

  • Apache YuniKornFree

Apache YuniKorn pricing →

HTCondor

No plans published.

HTCondor pricing →

In their own words

Apache YuniKorn

Apache YuniKorn is a resource scheduler for batch, data, and machine learning workloads on Kubernetes. It is a Kubernetes-compatible alternative to the default scheduler and is described as transparent to existing Kubernetes applications. Hierarchical queues provide fine-grained tenant controls that can reflect an organization’s structure. Scheduling features include gang scheduling, FIFO and Fair job ordering, resource fairness, reservations, and preemption. A web UI centralizes cluster capacity, utilization, and application information. YuniKorn exposes metrics through Prometheus, and project guidance covers monitoring with Prometheus and Grafana. The project recommends deployment to an existing Kubernetes cluster using its Helm chart and Helm 3 or later. The software is free under the Apache License 2.0. Releases include source tarballs, which must be built before use, and prebuilt Docker images. The project advises checking release artifacts for tampering with GPG or SHA-512. Help is available through the YuniKorn Slack #yunikorn-user channel or the user mailing list.

Visit yunikorn.apache.org

HTCondor

HTCondor is a free high-throughput computing system that coordinates networked machines to run submitted jobs. It finds available machines, matches their resource offers to job requirements and preferences through ClassAds, and can restart a job elsewhere if its current machine becomes unavailable. It is suited to submitting large batches, including thousands of runs across different data sets, and can use otherwise idle machines in a pool. Users do not need login accounts on machines running their jobs; file transfers and split execution support that model. HTCondor can draw on clusters, cloud resources, and international grids, and flocking can connect multiple installations. It supports transfers to and from S3-compatible storage, including Google Cloud Storage through its S3 interoperability API, but not entire buckets or directories. The software is licensed under Apache License 2.0, includes Python bindings, and offers user and administrator guides. Community support is available through a mailing list; paid contract support offers guaranteed resolution and faster turnaround. Security fixes cover current feature and LTS versions, with the previous LTS supported for approximately twelve months after a new LTS release.

Visit htcondor.com