durable-streams/durable-streams

Health v2 · maintenance only

Adoption not part of the score

1674 stars · 66 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Durable Streams is a protocol and tooling for persistent, addressable, real-time data streams over HTTP, with offset-based resumability, catch-up reads, and live tailing. It targets resilient AI agent sessions and collaborative multi-user, multi-agent systems, with clients in TypeScript and Python plus integrations like TanStack AI, Vercel AI SDK, and Yjs.

Use cases

• stream llm token responses with resume across reconnections
• build resilient agent sessions with replayable event streams
• stream tool outputs and progress events to clients
• sync database changes to web and mobile clients
• sync CRDTs for collaborative editing
• build event-sourced architectures with client-side replay
• tail streams live over sse with guaranteed delivery

When to choose

• you need ordered, replayable, resumable streams over plain http
• you are building agentic or collaborative AI apps that must survive reconnects
• you want exactly-once delivery semantics to browsers, mobile, or native clients
• you want integrations with TanStack AI, Vercel AI SDK, or Yjs

When to avoid

• you need a full message broker with queues, routing, and fan-out like kafka or rabbitmq
• your use case is simple request/response without durability or replay
• you need non-http transports or strict low-latency intra-cluster messaging

Facets

library · maturity active

streaming http-server http-client message-queue sdk cli microservices developer-tools apis large-language-models python cross-platform cli durable-streams agent-loop resumable-streams event-sourcing collaborative-ai offset-based-resumability live-tailing tanstack-ai vercel-ai-sdk yjs-provider ai-agents real-time typescript nodejs web-server

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markdown · JSON · MCP: product_card(name="durable-streams/durable-streams")