Scheduling

Cal.diy49.7k★

Cal.diy is what's left of open source Cal.com. In April 2026 Cal.com moved its production code to a private repo, renamed the public one Cal.diy, stripped out every enterprise feature, and relicensed what remained from AGPL to MIT. You get the core scheduling: booking pages, availability, the app store integrations and API v2, self-hosted. It needs Node 18+ and Postgres 13+. The README points at a cal.diy Docker image, but none was published when we checked, so plan to build it yourself with the included compose file. There's been no tagged release since the split; the latest is still the pre-fork v6.2.0 from March. Former Cal.com interns maintain it while Cal.com's engineers work on the closed product. Cal.diy is free, and its README recommends it for personal, non-production use. Teams, organizations, routing forms, workflows, SSO, insights and API v1 are gone; they live only in Cal.com's closed cloud, which is free for individuals, Teams at $16 per user a month ($12 billed annually), Organizations at $37 ($28 annually), Enterprise custom. Solo users who want to own their booking page: fine. Anyone needing team scheduling: this isn't it. The catch: this is a fork in maintenance mode, not a product with a roadmap. With no releases since the split, you're running community code that drifts further from Cal.com every month.

Airflow47.4k★

Airflow is the industry standard for scheduling and running data pipelines: pulling data from APIs, transforming it, loading it into warehouses, sending reports. Basically cron jobs with a brain: a web UI that shows you every pipeline, every run, what succeeded, what failed, and why. What's free: Everything. Apache 2.0 license, fully open source, no premium features gated behind a paywall. The entire platform is yours. Airflow powers data pipelines at Airbnb (where it was created), Lyft, Twitter, and thousands of other companies. The DAG model (directed acyclic graph, basically a flowchart of tasks) is proven. The plugin ecosystem is massive. If a data source exists, someone's written an Airflow connector for it. The catch: Airflow is complex. Self-hosting means managing a web server, scheduler, workers, a metadata database, and message queue. A production deployment is not a weekend project. The Python-based DAG definitions are powerful but have a steep learning curve. And the scheduler can be resource-hungry. Plan for 4GB+ RAM minimum for anything beyond toy pipelines.

xxl-job30.7k★

Scheduled jobs scattered across servers as individual crontabs become impossible to see or control. Xxl-job handles that. It's essentially a centralized cron server with a web UI: you register your jobs, set schedules, and the platform distributes execution across your executor nodes. GPL-3.0 licensed. The admin panel shows job status, execution logs, running tasks, and lets you trigger, pause, or kill jobs manually. Supports CRON triggers, fixed-rate triggers, and API triggers. Built-in retry, timeout, failover, and sharding strategies. Fully free. No paid tier. This is a Chinese open source project (documentation is primarily in Chinese) widely used in Chinese tech companies. The catch: GPL-3.0 means derivative works must also be GPL. Check if that's compatible with your project. Documentation and community are primarily Chinese-language. If you don't read Chinese, you'll rely on machine translation and English blog posts. The architecture requires a separate admin server (MySQL-backed) alongside your executor nodes, which adds operational complexity.

Dagster16.4k★

Instead of defining tasks and dependencies, you define data assets (the things your pipelines produce) and Dagster figures out what needs to run and when. What's free: The open source orchestrator is fully free. Apache 2.0 license. All core features included: asset definitions, scheduling, sensors, partitions, IO managers. The asset-based approach is Dagster's real innovation. Instead of thinking 'run task A then task B,' you think 'I need this dataset to be fresh.' Dagster handles the rest. The local development experience is excellent. Run dagster dev and you get a full UI instantly. Testing data pipelines is actually pleasant, which is rare. The catch: Dagster Cloud is where they make money, and some features nudge you toward it. The open source version requires you to manage your own deployment (Kubernetes, Docker, or a daemon). The community is smaller than Airflow's, so you'll find fewer Stack Overflow answers. And if your team already knows Airflow, the mental model shift to asset-based thinking takes real effort.

dolphinscheduler14.6k★

Data pipelines need something to decide what runs, in what order, and what happens when a step fails. DolphinScheduler handles that. Basically, it's a visual workflow scheduler where you drag and drop tasks into a pipeline and it manages dependencies, retries, and scheduling. It is an Apache project backed by a real community. Supports tasks in Python, Shell, SQL, Spark, Flink, and more. The visual DAG editor makes it accessible to people who are not writing code for a living. The catch: it is Java-based and the self-hosted setup is not trivial; you need ZooKeeper and a database. The UI is functional but dated compared to newer tools like Dagster or Prefect. And the documentation has rough patches, especially for non-Chinese-speaking users (the project originated in China).

quartznet7.1k★

Quartz.NET is the job scheduler .NET developers reach for when a basic timer is not enough. It runs recurring or one-off background tasks inside your own application, with cron-style triggers, persistence, and clustering so jobs survive restarts and spread across machines. It is a port of the long-running Java Quartz project, Apache-2.0, free, and shipped as a NuGet package. The simple case (fire this method every five minutes) is easy. Durable, clustered scheduling is where the work shows up: you stand up a database-backed job store and tune it so jobs are not lost or double-fired. That is the right trade for reliability, but it is more involved than the quick-start makes it look. Plan for a real backing store the moment you care about jobs running exactly once. This is for .NET teams that need dependable scheduling baked into their app rather than an external cron box or Windows Task Scheduler. Solo projects: free and fine with the in-memory store. Teams running anything that must not drop a job: free still, but invest in the persistent store and test failover. If you are not on .NET, this is not your tool. The catch is the ecosystem lock. Quartz.NET is excellent and also .NET-only, so it solves nothing if your stack lives elsewhere. And the clustered setup, while solid, is not something you wire up in five minutes.

Radicale5.2k★

Radicale is a calendar and contacts server you run yourself. When you want your events and address book off Google or Apple but still synced across your phone, laptop, and desktop, this is the piece that does it. It speaks CalDAV and CardDAV, the standard protocols every major calendar and contacts client already supports, and it stores everything as plain files on disk. No database, no heavy stack. It is famously easy to stand up: a Python install and a small config, and you have a working server. Production hardening is where it climbs to moderate, since you will want TLS, real authentication, and a reverse proxy in front of it. But there is no database to babysit and the data is just files you can back up with anything. Radicale is GPLv3 and completely free, with no paid tier or hosted option. The trade is that you become the host. Baikal is a similar single-purpose option, and when you want calendar and contacts as part of a bigger self-hosted suite with a web UI, Nextcloud or SOGo cover more ground. Solo users and families are the sweet spot. Small teams can run it happily; larger orgs usually want the broader suite instead. The catch is scope. Radicale does calendar and contacts and nothing else, and there is no friendly web app for end users to click around in. You manage everything through a client, and uptime and backups land entirely on you.

easyappointments4.5k★

Easy!Appointments gives a business a booking page customers actually use: services, staff schedules, working hours, Google Calendar sync, and email notifications. It's the self-hosted answer to appointment scheduling, GPL v3, free with no per-seat fees and no commission on bookings. It runs on the most boring stack on the internet: PHP and MySQL on any cheap shared host or small VPS. That's a feature. No containers required, upgrades are a file swap plus a migration script, and any web agency on earth can maintain it for you. Solo service businesses and small shops: this replaces a Calendly bill if you're willing to host a PHP app. Developers booking meetings rather than customer appointments should use calcom/cal.com instead; it's built for meeting links and integrations, not service businesses. The maintainer sells installation, managed hosting, and customization if you'd rather pay someone. The catch: it's appointment booking, not a scheduling platform. No routing forms, no round-robin across a sales team, and the interface is functional rather than polished. It does one job from 2015 exceptionally cheaply.

croner2.6k★

Croner is a tiny cron expression parser and scheduler for JavaScript and TypeScript. No external dependencies, no system cron, no database. It runs in your Node.js process, Deno, Bun, or even the browser. TypeScript, MIT. The selling point is zero dependencies and correctness. It handles standard cron syntax plus extensions like seconds-level precision and the L flag (last day of month). It's timezone-aware out of the box, which is the thing that trips up most cron libraries. Fully free. No paid tier, no cloud service. It's a library. You npm install it and call it from your code. Solo to large teams: free. The library weighs almost nothing and does exactly one thing well. The catch: croner runs inside your process. If your app crashes, your schedules stop. For production workloads that absolutely cannot miss a scheduled run, you need a proper job queue with persistence (BullMQ with Redis, or a system-level cron job. Croner is perfect for in-process scheduling where a missed run isn't catastrophic. It's not a replacement for distributed job infrastructure.

go-quartz2.0k★

Go-quartz is a lightweight in-process job scheduler. Basically, it's cron but embedded directly in your Go app, no external dependencies needed. It supports cron expressions, fixed-interval scheduling, and one-off delayed jobs. Jobs run in goroutines, so they're concurrent by default. The API is clean: create a scheduler, define a job, set a trigger, start. That's it. It's fully free under MIT. No paid tier, no cloud version, no strings. It's a library you import and use. go-quartz is the right choice when your scheduling needs are simple and you don't need durability. Once you need jobs to survive restarts or run across multiple instances, you've outgrown it. The catch: it's in-process only. If your app restarts, all scheduled state is lost; there's no persistence layer. For durable job scheduling where jobs survive restarts and can be distributed across multiple instances, you need something heavier. Temporal handles complex workflow orchestration. For simpler persistent job queues, look at something like River (for Postgres-backed Go jobs) or Asynq (Redis-backed).

gocron627★

Gocron is a lightweight cron job runner written in Go that gives you a web UI to manage it all. Instead of editing crontab files on a server and hoping you got the syntax right, you get a dashboard where you can create, pause, and monitor scheduled jobs. It's small, fast, and self-hosted only. MIT licensed. This is a focused tool, not a platform. You define jobs (shell commands or HTTP calls), set the schedule, and gocron handles execution and logging. The web UI shows run history and status at a glance. Everything is free. No paid tier, no cloud offering. You run it in Docker or as a binary. The catch: this is nascent, and a 2. The community is tiny, so if you hit a bug you're largely on your own. For serious production scheduling with retries, dependencies, and alerting, you want something heavier. But for a homelab or small server where you just need cron with a UI, gocron nails it.