OpenComputer vs Supernova: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of OpenComputer and Supernova — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
OpenComputer
Digger
Deploy managed AI agents as persistent, always-on cloud VMs with steerable execution and permanent HTTP endpoints.
Key features
- Persistent VMs: Always-on virtual machines with a full filesystem and OS access that survive restarts, so agent state is exactly where you left it.
- Elastic Compute: Resize memory (1-16 GB) and vCPU while a VM is running to match the workload of the agent harness.
- Instant Checkpoints: Snapshot any VM state to fork or roll back in seconds, recovering from bad agent runs without teardown.
- One-Prompt Deploy: Paste a single prompt into Claude Code, Codex, or Cursor to install the CLI, log in, initialize, and deploy an agent end-to-end.
- Permanent Agent URLs: Every deployed agent gets a stable HTTP endpoint reachable from Slack, webhooks, and cron jobs.
- Steerable Mid-Run: Interrupt and redirect long-running agents without killing the session, keeping durable state intact.
- Hibernate & Wake: Pause idle VMs to stop paying for compute and resume them instantly when the agent is needed again.
Best for
- Shipping B2B Agent Platforms: Provide end users of your Lovable/Devin/Bolt-style product with per-user VMs that remember installed dependencies and files across sessions.
- Long-Running Autonomous Tasks: Run overnight research, scraping, or refactor agents that need to persist context across many hours without a sandbox timeout.
- Slack & Cron-Triggered Agents: Wire a permanent agent URL to a Slack app or cron so a team can invoke the same agent state from anywhere.
- Rapid Agent Prototyping from an IDE: Turn a natural-language prompt inside Claude Code or Cursor into a live, invokable agent without provisioning infrastructure.
- Safe Rollbacks for Autonomous Coders: Use checkpoints to fork an agent VM before risky changes and restore instantly if the agent breaks its environment.
Supernova
Supernova
An encrypted Iceberg data lake with a built-in engine and MCP endpoint, so Claude and Codex can query every tool your company uses.
Key features
- MCP Endpoint for Claude and Codex: Point any MCP-speaking assistant at mcp.supernova.ai/mcp and every synced table becomes queryable in natural language.
- Encrypted Iceberg Lake: Open Apache Iceberg tables in object storage with table-level encryption, so the data stays in a portable open format you control.
- Zero-Copy Connections: Any engine that speaks Iceberg can read the lake directly, avoiding a second copy of your warehouse.
- Time Travel: Every table retains version history, so you can query the state of your data as of any earlier point.
- Built-In Frontier Models: Ask a question or describe a dashboard in plain language and Supernova generates the models and visualisations without a data team.
- TypeSQL: Schema-aware SQL that autocompletes across joins and type-checks before execution, catching errors the way a typed language would.
- Single-Binary CLI: One command-line tool connects sources, runs queries, tails live table changes and registers the MCP endpoint with Claude Desktop, from a laptop or CI.
- Git-Backed Dashboards: Models and dashboards are readable and writable through Git, putting analytics artefacts under normal version control.
Best for
- Conversational Revenue Analysis: Ask Claude which customers churned last quarter and why, with the answer computed over live Stripe and HubSpot tables.
- Warehouse Cost Reduction: Replace a multi-vendor pipeline-plus-warehouse stack with one usage-billed platform, which the vendor illustrates as $5,640/mo dropping to $540/mo for a hardware company.
- Dashboards Without a Data Team: Describe the dashboard you want in a sentence and have the models and charts generated for you.
- AI-Native Data Access Layer: Give internal agents a governed, encrypted single endpoint for company data instead of per-tool API integrations.
- Auditing Historical State: Use table version history to reconstruct what the numbers looked like before a pricing or schema change.
- CI-Driven Data Workflows: Drive connections, queries and change tailing from pipelines using the single CLI binary.