DeepSpace vs. Convex

DeepSpace is a full-stack SDK and hosting platform: one npm package gives a React + TypeScript app auth, a real-time database, presence, collaborative editing, file storage, and Stripe payments, and one command — npx deepspace deploy — ships the whole app to <name>.app.space. DeepSpace is laying the foundation for rebuilding the Internet in an AI-native way.

DeepSpace is designed for AI coding agents. New projects install an agent skill, the CLI is scriptable with --json output, and the decisions agents get wrong — permission checks, identity verification, payment flows — are made once inside the SDK instead of regenerated per project.

Convex is a reactive backend platform for TypeScript developers. You write queries, mutations, and actions in TypeScript; every mutation runs as a transaction; and client queries update automatically over WebSockets whenever the data they depend on changes. File storage, scheduled functions, full-text search, and vector search are built in.

The Convex backend is source-available under the Functional Source License (FSL) — each release becomes Apache 2.0 after two years — and can be self-hosted with Docker. As of July 2026, Convex also ships AI-focused components (agents, workflows, RAG) and Chef, its AI app builder.

The main difference is where the platform stops: Convex stops at the backend, while DeepSpace carries the app all the way to a live URL. Convex offers deeper database semantics — transactional mutations, serializable isolation, reactive queries — while DeepSpace offers a wider slice of the product: hosting, auth, payments, domains, and prebuilt collaboration features.

Yes, when you are shipping a complete app. npx deepspace deploy puts the frontend, backend, auth, and payments live at <name>.app.space in one step, with no other accounts to create.

Convex deploys its backend just as smoothly, but the backend is where it stops: as of July 2026 its production docs point frontends to hosts like Vercel or Netlify, and full-featured auth usually means adding Clerk, Auth0, or WorkOS. A typical production Convex app is therefore a three-service stack — backend, frontend host, auth provider. If you already run that stack happily, Convex slots in cleanly.

Both are real-time by default — this is the strongest part of both platforms — but they excel at different layers. Convex's sync engine is the deeper database: every mutation is a transaction, queries are deterministic and cached, and all subscribed clients update to the same consistent snapshot. For workloads where cross-document invariants matter, that consistency story is best-in-class.

DeepSpace syncs shared records to React hooks and layers prebuilt collaboration on top: presence, live cursors, conflict-free (CRDT-based) collaborative text, and shared whiteboards ship as ready-made rooms. On Convex you would assemble those features from reactive queries and components; on DeepSpace they are wiring. Pick by workload: deep transactional logic favors Convex, multiplayer product surfaces favor DeepSpace.

DeepSpace includes auth; Convex usually delegates it. DeepSpace ships sign-in with Google, GitHub, and email/password, with sessions handled by the platform, plus role-based permissions declared next to each collection's schema and enforced server-side.

Convex Auth is still in beta as of July 2026, and Convex's own docs recommend third-party providers — Clerk, Auth0, or WorkOS — for full-featured authentication. Those providers are excellent, and they are another service and another bill. Authorization in Convex is code you write inside your functions: maximally flexible, with no declarative permission layer checking it.

DeepSpace has payments built in; Convex has no first-party payments product as of July 2026. In DeepSpace you declare subscription plans or one-time products in code, they sync to Stripe on deploy, and prebuilt hooks and components handle checkout and entitlements, with refund and cancellation helpers in the server SDK.

On Convex, payments are an integration you own — Stripe calls from actions, webhook endpoints via HTTP actions, and entitlement records you model and protect yourself, or a community component that covers part of the flow.

Both platforms take AI seriously; they aim at different jobs. Convex ships an Agent component for building AI features into your product — persistent threads, durable workflows, RAG — and Chef, its own AI app builder that generates Convex apps.

DeepSpace is agent-first at the platform level: the SDK ships as a skill your coding agent loads, the whole stack sits behind one login and one CLI, and security-critical behavior is enforced by the platform rather than left to generated code. The practical difference: Convex gives an agent strong backend building blocks; DeepSpace gives an agent the entire shipping path — build, auth, payments, deploy, live URL — inside one system.

Both are free to start. DeepSpace is free to start building and deploying, and paid plans add more deployed apps and usage as you scale.

Convex's free tier, as of July 2026, includes 1 million function calls per month and 0.5 GB of database storage, with a pay-as-you-go Starter option beyond that. The Professional plan is $25 per developer per month with 25 million function calls included and metered overages across function calls, storage, egress, compute, and search. The per-developer component means Convex costs compound with team size; the per-unit metering means they compound with traffic. Both are published and predictable to model.

Choose Convex when your hardest problem is server-side data logic. If you need transactions with serializable isolation, deterministic server functions, built-in full-text or vector search, or the option to self-host your backend, Convex is the stronger fit as of July 2026. It is also natural if you already deploy frontends to Vercel and use Clerk for auth — Convex is designed to complete exactly that stack.

Choose DeepSpace when you want the whole product shipped from one place — a real-time collaborative web app with auth, payments, domains, and hosting included — especially when an AI agent is doing the building.