Rivet

Use Cases

One primitive that adapts to agents, workflows, collaboration, and more.

• AI Agent — Each agent runs as its own actor with persistent context, memory, and the ability to schedule tool calls.
• Sandbox Orchestration — Coordinate sandbox sessions, queue work, and schedule cleanup in one long-lived actor per workspace.
• Workflows — Multi-step operations with automatic retries, scheduling, and durable state across steps.
• Collaborative Documents — Real-time collaborative editing where each document is an actor broadcasting changes to all connected users.
• Per-Tenant Database — One actor per tenant with low-latency in-memory reads and durable tenant data persistence.
• Chat — One actor per room or conversation with in-memory state, persistent history, and realtime delivery.

Integrations

Serverless, containers, or your own servers — Rivet Actors work with your existing infrastructure, frameworks, and tools.

Infrastructure: Vercel • Railway • AWS • Docker

Frameworks: React • Next.js • Hono • Express • Elysia • tRPC

Runtimes: Node.js • Bun • Deno

Tools: Vitest • Pino • AI SDK • OpenAPI • AsyncAPI

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How Actors Compare

Rivet Actors vs. Traditional Infrastructure

State

<details> <summary>Benchmark details & methodology</summary>

Cold Start - Rivet Actor (~20ms): Includes durable state init, not just a process spawn. No actor key, so no cross-region locking. Measured with Node.js and FoundationDB. - Kubernetes Pod (~6s): Node.js 24 Alpine image (56MB compressed) on AWS EKS with a pre-provisioned m5.large node. Breakdown: ~1s image pull and extraction, ~3-4s scheduling and container runtime setup, ~1s container start. - Virtual Machine (~30s): AWS EC2 t3.nano from launch to SSH-ready, using an Amazon Linux 2 AMI. t3.nano is the smallest available EC2 instance (512MB RAM).

Memory Per Instance - Rivet Actor (~0.6KB): RSS delta divided by actor count, measured by spawning 10,000 actors in Node.js v24 on Linux x86. - Kubernetes Pod (~50MB): Minimum idle Node.js container on Linux x86: Node.js v24 runtime (~43MB RSS), containerd-shim (~3MB), pause container (~1MB), and kubelet per-pod tracking (~2MB). - Virtual Machine (~512MB): AWS EC2 t3.nano, the smallest available EC2 instance with 512MB allocated memory.

Read Latency - Rivet Actor (0ms): State is read from co-located SQLite/KV storage on the same machine as the actor, with no network round-trip. - Redis (~1ms): AWS ElastiCache Redis (cache.t3.micro) in the same availability zone as the application. - Postgres (~5ms): AWS RDS PostgreSQL (db.t3.micro) in the same availability zone as the application.

Idle Cost - Rivet Actor ($0): Assumes Rivet Actors running on a serverless platform. Actors scale to zero with no idle infrastructure costs. Traditional container deployments may incur idle costs. - Virtual Machine (~$5/mo): AWS EC2 t3.nano ($0.0052/hr compute + $1.60/mo for 20GB gp3 storage) running 24/7. t3.nano is the smallest available EC2 instance (512MB RAM). - Kubernetes Cluster (~$85/mo): AWS EKS control plane ($73/mo) plus a single t3.nano worker node with 20GB gp3 storage, running 24/7.

Horizontal Scale - Rivet Actors (Infinite): Scale linearly by adding nodes with no single cluster size limit. - Kubernetes (~5k nodes): Officially supports clusters of up to 5,000 nodes per the Kubernetes scalability documentation.

Multi-Region - Rivet (Global edge network): Automatically spawns actors near your users and handles routing across regions.

</details>