Rivet gives you stateful actors to build on. Avalanche runs the work your agents do.

Quick answer

Updated October 28, 2026. Rivet and Avalanche are both open source and both make multi-step work survive crashes, but they work at different levels.[1, 4, 20] Choose Rivet if developers are building a stateful backend in TypeScript or Rust: one long-lived Actor per agent, user, room or tenant, with its own SQLite database, realtime WebSocket connections and scheduling, and a cloud with a free tier, BYOC or full self-hosting.[1, 2, 3] Choose Avalanche if the job is a long, multi-step, document-heavy business workflow: you set the few steps, checks and approvals that matter, agents do the work inside each step, and every run keeps typed step outputs and versioned files your team can compare across runs and versions, with instant rollback on Avalanche Cloud.[21, 23, 25]

Key takeaway

Choose Avalanche when agents should do the work inside a few business steps you control, often over PDFs, Word files and spreadsheets.

Choose Rivet when developers are building a realtime or per-tenant stateful backend and want actors they can run anywhere today.

  • Avalanche wins on level of abstraction: you set the steps, checks and approvals; an agent does the work inside each step, instead of actors, actions and workflow steps you write in TypeScript.
  • Avalanche wins on versions and rollback: Avalanche Cloud makes a previous version of the whole workflow live again instantly, from the console or one command, with no rebuild and no worker redeploy; Rivet rolls a worker pool out to an earlier build, and self-hosted versions only go up.
  • Rivet wins on availability today: Rivet Cloud has a free tier, the Apache 2.0 control plane is self-hostable in full, and BYOC is available; Avalanche Cloud is on a waitlist.

By , CTO, Trampoline AI. Updated · Facts checked · Published by the Avalanche team. Avalanche competes with Rivet.

01 / The core differenceAvalanche vs Rivet

A primitive to build your backend, or agentic workflows for your business.

Rivet gives developers a primitive for stateful backends: Actors with durable state, queues, realtime connections and scheduling, plus Workflows, Agents and sandboxes built on them.[1, 14] Avalanche works a level higher: you describe the outcome and the few steps, checks and approvals that matter, and agents do the work in between, with each step checkpointed.[21, 25]

Rivet is infrastructure for developers: it schedules, routes and persists stateful Actors that your TypeScript or Rust code defines, and its Workflows, Agents and sandboxes are built on those Actors.[1, 4, 14] Avalanche is built for the work agents do for a business: you define the few steps, checks and approvals that matter, agents do the work in between, and every run keeps its version, its typed step outputs and the files each step changed.[21, 23, 25] Both let you inspect a run step by step; Rivet's inspector helps a developer debug one Actor's run, while Avalanche's step outputs let a team compare the results of agent work across many runs and versions.[4, 25]

02 / At a glanceChecked 2026-10-28

Avalanche and Rivet, side by side.

Avalanche and Rivet compared, checked 2026-10-28
CriterionAvalancheRivetEdge
Level of abstractionCoarse business steps: you set the steps, checks and approvals, and an agent does the work inside each step.[20, 25]A developer writes Actors, actions and workflow steps in TypeScript or Rust; an agent is an Actor running the Pi harness, prompted from a workflow step.[4, 11, 14]Avalanche edge
Agent steps and skillsAgent steps declare typed inputs and outputs, can run Claude through the Claude Agent SDK and load Agent Skills (SKILL.md); the Avalanche skill drafts a full workflow from a described outcome.[22, 26, 27]A workflow step prompts an agent Actor and gets its text answer; SKILL.md files load through an extension you add; npx skills add rivet-dev/skills teaches coding agents Rivet.[1, 11, 12]Avalanche edge
Document lineageAvalanche Cloud: every run gets a versioned workspace; each step's file changes are committed as a new version, so you can see which step changed a file, compare versions and download any step's files; agent steps get PDF, Word and spreadsheet skills.[23, 25]Every Actor gets a SQLite database and a POSIX filesystem tiered to S3; agentOS VMs can export a filesystem snapshot. Per-step file versions within a run are not documented.[1, 30]Different jobs
Inspecting and comparing runsAvalanche Cloud: typed inputs and outputs at every step checkpoint, in one run history filtered by status, flow and deployment; a web console with a live DAG of every flow and run, and the full console in your terminal, so you can compare a step across many runs and versions.[21, 25]The dashboard's run inspector shows each step's status, timing, attempts, inputs, outputs and errors in a visual DAG and can replay eligible steps; OpenTelemetry traces; Rivet MCP lets an AI client inspect a run.[4, 19]Different jobs
Versions and rollbackAvalanche Cloud: each deploy is a frozen version of the whole workflow, mapped to an exact git commit, with locked, hash-verified dependencies; running workflows finish on the version they started on; instant rollback to any previous version from the CLI or console, no rebuild; an audit trail of who promoted or rolled back.[25]Rivet Cloud rolls back by deploying an earlier build ID: no rebuild, but the worker pool is rolled out to that image again. Self-hosted, versions only go up, so undoing a bad deploy means redeploying the old code under a higher version. Running workflows keep their version through replay and version gates you write.[5, 7, 8, 9, 32, 33]Avalanche edge
Startup and live updatesLive run streams and a live graph of every run in the console as steps start and finish. Per-step startup p50 1.13 s, measured October 27, 2026 on v0.6.6.[25]Rivet reports a 6.92 ms p50 cold start for a new Actor; Actors push events to connected app clients over WebSocket. The two figures time different things, and there is no head-to-head benchmark.[1, 14]Different jobs
Availability and self-hostingSelf-hostable MIT-licensed runtime with operator, web console, REST API and terminal UI, more limited than Cloud; Avalanche Cloud is on a waitlist.[20, 24, 28]Apache 2.0, self-hostable in full; Rivet Cloud with Free, Hobby and Team plans; BYOC in your VPC on Enterprise Edition. Rivet 3.0 is in preview; 2.x stays supported.[1, 3, 18, 34]Rivet edge
Schedules, triggers, CLI and APIAvalanche Cloud: cron schedules and webhooks declared in your workflow code, following rollbacks and promotions; webhook URLs never change on redeploy, and idempotency keys return the same run for 7 days; a typed REST API with an OpenAPI spec, and a CLI.[25]Per-Actor one-shot schedules and cron jobs that survive sleep, restarts and upgrades; Actors addressed over HTTP or WebSocket; an HTTP API with an OpenAPI spec, a CLI and Rivet MCP.[2, 8, 15]Similar
Identity and accessAvalanche Cloud: SSO; organization roles and per-action permissions, managed in your organization's settings; scoped, encrypted secrets; agents see only what each step passes them (its inputs, its files and the secrets it declares); steps run non-root in a sandbox; no spend limits yet.[25]Organization members managed in the dashboard; namespaces with their own tokens per environment or customer; JWT authentication for Actors; a role-based ACL API on Enterprise Edition, not yet in the 3.0 preview. SSO and audit logs are not documented.[16, 17, 18, 31]Similar
03 / Where each one winsOne claim per card

Where each one wins

Where Avalanche wins

  • Higher-level workflows

    You set the few business steps, checks and approvals that matter; an agent does real work inside each step. Python steps keep exact rules and arithmetic.[20, 25]

  • From a skill to a workflow

    Install the Avalanche skill with npx skills add Trampoline-AI/avalanche, describe the outcome in your coding agent, and it drafts the workflow with you.[22]

  • Every step versions your documents

    Avalanche Cloud gives every run a versioned workspace. Pass one document or hundreds; each step works on the files directly, and every step's changes are committed as a new version of the workspace, so you can see which step produced or changed each file, compare versions, and download any step's files. Document lineage, the way data teams have table lineage.[23, 25]

  • Versioned deploys and instant rollback

    On Avalanche Cloud each deploy is a frozen, checksum-verified version of the whole workflow, mapped to an exact git commit. Running workflows finish on the version they started on, and instant rollback makes any previous version live again instantly, from the console or one command, with no rebuild. Avalanche Cloud is on a waitlist.[25, 28]

  • Runs your business team can compare

    Each step is a business result with typed outputs, such as an RFP answer or a contract finding. Avalanche Cloud keeps every run by workflow and version, so you can compare one step across many runs.[21, 25]

  • Approvals built in

    Checks every run must pass and owner approval before results go out are part of the workflow on Avalanche Cloud, not a tool or queue you build.[25]

Where Rivet wins

  • Lightweight, long-lived actors

    An Actor hibernates when idle and wakes on demand; Rivet reports about 72 KB of memory per running Actor, so many tenants or sessions fit on one server.[1]

  • Live connections to your app users

    Clients hold a live WebSocket to an Actor, and the Actor broadcasts events to every connected client, with React hooks on the frontend. No separate realtime service.[1, 14]

  • One primitive for a whole backend

    One Actor per agent, session, user, room or tenant, each with its own SQLite database, queue and schedules, addressed by key. The same primitive covers agents, multiplayer apps and per-tenant databases.[2, 14]

  • Run it anywhere

    Apache 2.0 and self-hostable in full as one binary on Docker, Kubernetes or a VM, managed in your own VPC with BYOC, or on Rivet Cloud with a free tier.[1, 3, 18]

  • Long-lived, durable agents

    Each agent lives in its own Actor and SQLite database, so it can sleep, crash or upgrade mid-run and pick up where it left off; workflows sleep durably on timers and queue waits.[10, 29]

04 / Detailed comparison4 buyer questions

What changes for your team.

01

A backend primitive or business workflows?

Buyer question

Are you building a product backend, or automating work your team repeats every week?

Rivet is an orchestrator for stateful workloads. Where Kubernetes schedules pods, Rivet schedules Actors: long-lived processes with durable state, a SQLite database, a queue, realtime connections and scheduling, each addressed by key.[2] You create one Actor per agent, session, user or tenant, and build your backend from them; Rivet Workflows, Agents, agentOS sandboxes and Dynamic Apps are all Actors under the hood.[1, 14] It fits coding agents inside your product, collaborative apps, multiplayer state and per-tenant databases.

Avalanche is built for long, multi-step business work that agents do, such as drafting RFP answers from past proposals or reviewing a stack of contracts. You set the few steps, checks and approvals that matter, agents do the work in between, and simple workflows fit the same model. On Avalanche Cloud, workflows run for hours or days, and an owner approves results before they go out.[25] Rivet's own docs draw a similar line inside its product: use a workflow when the work has fixed steps, waits or retries, and a single agent session when the agent should decide the steps itself.[11]

02

Durability and recovery: close on both sides

Buyer question

What happens when a step fails halfway through a long run?

In Rivet Workflows, each step records its result the first time it runs; after a crash the workflow replays, recorded steps return their saved results, and the run picks up at the first step that never completed. Steps retry with backoff, failures can be handled as data, and rollback checkpoints run compensating actions. Code outside steps must be orchestration only, so replays stay deterministic.[4, 6] Workflows sleep durably on timers and queue waits, and an Actor whose machine fails moves to another with its state intact.[1, 29]

Avalanche Cloud records completed steps durably and does not re-run them after a crash; failed steps retry, and uncertain outcomes are held instead of blindly retried. Steps are ordinary Python or agent steps, with no determinism rule to follow between checkpoints.[21, 25]

03

Agents, documents and approvals

Buyer question

How much do you want to build around the agent yourself?

Rivet gives each agent its own Actor running the Pi harness, with its files in the Actor's SQLite database or in a sandbox such as E2B or Daytona when it needs a shell.[10] A workflow step can prompt that agent and wait for its answer.[11] Skills are SKILL.md files loaded by an extension you add, and approvals are code you write: Rivet's human-in-the-loop guide puts the check inside a tool, because Pi has no built-in approval flow.[12, 13]

In Avalanche, agent steps declare typed inputs and outputs and get PDF, Word and spreadsheet skills, and on Avalanche Cloud each step's file changes are committed as a new version of the run's workspace.[21, 23, 25] The Avalanche skill drafts the workflow from an outcome you describe in your coding agent.[22] Agent steps can run Claude through the Claude Agent SDK and load Agent Skills (SKILL.md), and owner approval before results go out is part of the workflow.[25, 26, 27]

04

Running it in production

Buyer question

How mature does the managed service need to be today, and how do you undo a bad release?

Rivet has the edge on availability and deployment choice. Rivet Cloud has a free tier and paid plans, the Apache 2.0 control plane self-hosts as one binary, and Enterprise Edition adds BYOC, an ACL system and SQLite backups.[3, 18, 34] Rivet 3.0, released in preview on October 26, 2026, moves storage onto S3-backed disks; multi-region, serverless and ACLs stay on 2.x until 3.0 leaves preview.[18] Rollback is where the models differ. On Rivet Cloud you roll back by deploying an earlier build ID, which skips the Docker build but rolls the worker pool out to that image again; self-hosted, version numbers only go up, so undoing a bad deploy means redeploying the old code under a new, higher version.[7, 8, 9, 32, 33]

You can self-host the MIT-licensed Avalanche runtime, with its operator, web console, REST API and terminal UI, on your own infrastructure; it is more limited than Avalanche Cloud, which runs the production infrastructure for you.[20, 24] Avalanche Cloud adds SSO and organization roles, versioned deploys, instant rollback of the whole workflow to any previous version with no rebuild or worker redeploy, step checkpoints, managed queueing and one run history for every deployed workflow, and is open through a waitlist.[25, 28] Both let you inspect a run; the difference is what a step is. A Rivet step is code a developer wrote, so its inspector helps debug one run. An Avalanche step is a business result an agent produced, with typed outputs and versioned files, so a team can compare that step across hundreds of runs and see which outputs drift or which version changed them.[19, 21, 25]

05 / FAQDirect answers

Common questions.

Is Avalanche an alternative to Rivet?
Partly. Both are open source and make multi-step work durable.[2, 20] Rivet is a primitive for stateful, realtime backends, with Workflows and Agents built on its Actors; Avalanche runs business workflows where agents work inside a few steps you set, with versioned deploys and document lineage on Avalanche Cloud.[1, 25] The two can work together: a product built on Rivet keeps each user's live session in an Actor and, when a user uploads a contract, calls an Avalanche workflow through its API or a webhook to extract the terms, draft a review and wait for an owner's approval.
Does Rivet support rollback?
Partly. On Rivet Cloud, rivet deploy --build <build-id> rolls a worker pool out to an earlier build without rebuilding the image.[8, 9] When self-hosting, Rivet's docs say versions only go up: to undo a bad deploy, redeploy the previous code with a new, higher version number.[7, 32] Rollback in Rivet Workflows' failure docs means compensating actions inside a run, not returning to an earlier version.[6] Avalanche Cloud rolls a whole workflow back to any previous version instantly, from the console or one command, with no rebuild or worker redeploy, and running workflows keep the version they started on.[25]
Can Rivet run AI agents?
Yes. Each agent on Rivet is an Actor running the Pi harness, with durable conversations, optional sandboxes and OpenTelemetry tracing, and a workflow step can prompt an agent and wait for its answer.[10, 11]
Is Rivet open source?
Yes. Rivet is Apache 2.0 licensed and self-hostable in full; Rivet Cloud runs the same control plane.[1, 2] The Avalanche runtime is MIT-licensed on GitHub.[20]
How much does Rivet cost?
Rivet Cloud has a Free plan at $0 a month with hard limits (100,000 Awake Actor Hours, $5 of compute), Hobby from $20 a month plus usage and Team from $200 a month plus usage; beyond plan limits, usage costs $0.05 per 1,000 Awake Actor Hours, $0.40 per GB-month of state and $1 per million writes, and compute is billed per vCPU-second. Enterprise Edition is priced by sales, and self-hosting is free. Prices as of Oct 28, 2026.[3]
Can I see which step changed a document?
Yes, on Avalanche Cloud. Every run gets a versioned workspace, and each step's changes are committed as a new version, so you can see which step produced or changed each file, compare versions and download any step's files.[25] Rivet gives each Actor a durable SQLite database and filesystem; its docs do not describe per-step versions of files within a run.[1, 30]
06 / SourcesChecked 2026-10-28

Public primary sources.

Every source was fetched on the date shown. Prices and plans change; check the vendor before you buy.

  1. [1]Rivet home pageRivet · Checked https://rivet.dev/
  2. [2]rivet-dev/rivet repository and README (Apache 2.0 License)Rivet on GitHub · Checked https://github.com/rivet-dev/rivet
  3. [3]Rivet Cloud pricingRivet · Checked https://rivet.dev/pricing
  4. [4]Workflows (Rivet docs)Rivet · Checked https://rivet.dev/workflows/docs/
  5. [5]Versioning and migrations (Rivet Workflows docs)Rivet · Checked https://rivet.dev/workflows/docs/versioning/
  6. [6]Failure and recovery (Rivet Workflows docs)Rivet · Checked https://rivet.dev/workflows/docs/failure-and-recovery/
  7. [7]Versions and upgrades (Rivet docs)Rivet · Checked https://rivet.dev/docs/versions/
  8. [8]CLI (Rivet docs)Rivet · Checked https://rivet.dev/docs/cli/
  9. [9]Actor nodes on Rivet Cloud (Rivet docs)Rivet · Checked https://rivet.dev/docs/deploy/cloud/compute/
  10. [10]Agents (Rivet docs)Rivet · Checked https://rivet.dev/agents/docs/
  11. [11]Agents in workflows (Rivet docs)Rivet · Checked https://rivet.dev/agents/docs/workflows/
  12. [12]Agent skills (Rivet docs)Rivet · Checked https://rivet.dev/agents/docs/skills/
  13. [13]Human in the loop (Rivet Agents docs)Rivet · Checked https://rivet.dev/agents/docs/human-in-the-loop/
  14. [14]Actors (Rivet docs)Rivet · Checked https://rivet.dev/actors/docs/
  15. [15]Schedule and cron (Rivet Actors docs)Rivet · Checked https://rivet.dev/actors/docs/schedule/
  16. [16]Namespaces (Rivet docs)Rivet · Checked https://rivet.dev/docs/namespaces/
  17. [17]Role-based access control, Enterprise (Rivet docs)Rivet · Checked https://rivet.dev/docs/deploy/self-host/control-plane/rbac/
  18. [18]Introducing Rivet 3.0 Preview (Rivet changelog, October 26, 2026)Rivet · Checked https://rivet.dev/changelog/2026-10-26-introducing-rivet-3-0-preview/
  19. [19]Introducing Rivet Workflows (Rivet changelog)Rivet · Checked https://rivet.dev/changelog/2026-02-24-introducing-rivet-workflows/
  20. [20]Avalanche repository and README (MIT License)Trampoline AI · Checked https://github.com/Trampoline-AI/avalanche
  21. [21]Results, cancellation, and reruns (Avalanche docs)Avalanche docs · Checked https://avalanche-docs.docsalot.dev/build-workflows/results-and-reruns
  22. [22]Build a workflow with the Avalanche skill (Avalanche docs)Avalanche docs · Checked https://avalanche-docs.docsalot.dev/build-workflows/build-with-skill
  23. [23]Skills for agent steps: PDF, DOCX and spreadsheet (Avalanche docs)Avalanche docs · Checked https://avalanche-docs.docsalot.dev/agent-steps/skills
  24. [24]Architecture and current limits (Avalanche docs)Avalanche docs · Checked https://avalanche-docs.docsalot.dev/reference/architecture-and-limits
  25. [25]Avalanche and Avalanche Cloud overviewAvalanche · Checked https://avalanche.run/
  26. [26]Pull request #124: Claude Agent SDK agent stepsTrampoline AI on GitHub · Checked https://github.com/Trampoline-AI/avalanche/pull/124
  27. [27]Pull request #136: Agent Skills (SKILL.md) in agent stepsTrampoline AI on GitHub · Checked https://github.com/Trampoline-AI/avalanche/pull/136
  28. [28]Avalanche Cloud waitlistAvalanche · Checked https://cloud.avalanche.run/waitlist
  29. [29]Timers and concurrency (Rivet Workflows docs)Rivet · Checked https://rivet.dev/workflows/docs/timers-and-concurrency/
  30. [30]Filesystem (Rivet agentOS docs)Rivet · Checked https://rivet.dev/agentos/docs/filesystem/
  31. [31]Dashboard redesign: members and settings (Rivet changelog)Rivet · Checked https://rivet.dev/changelog/2026-05-20-dashboard-redesign/
  32. [32]Versions only go up; redeploy previous code with a higher version (versions.mdx)Rivet on GitHub · Checked https://github.com/rivet-dev/rivet/blob/677e9e897bb6b7cfa403fdb485ce804700b97e1f/docs/general/content/versions.mdx#L14
  33. [33]Roll back by deploying an earlier build ID (cli.mdx)Rivet on GitHub · Checked https://github.com/rivet-dev/rivet/blob/677e9e897bb6b7cfa403fdb485ce804700b97e1f/docs/general/content/cli.mdx#L44
  34. [34]Rivet Enterprise EditionRivet · Checked https://rivet.dev/enterprise/
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See the runtime for yourselfOpen source · MIT

Our code speaks for itself.

The Avalanche runtime is open source under the MIT License. Read the code, run the starter project, and see how it fits the work your team repeats.