Choosing authorization infrastructure is a high-stakes decision with real lock-in. We compare InferaDB, OpenFGA, SpiceDB, and Oso on performance, security, pricing, and operational burden — honestly.
Broken access control is the #1 API security risk — and most organizations still treat authorization as application logic, not infrastructure. A practical guide for security leaders evaluating fine-grained authorization.
Choosing authorization infrastructure locks you in for years. Here's a structured evaluation framework covering performance, security, compliance, pricing, and lock-in risk — the questions to ask and what good answers look like.
You started with a user_roles table. Now you have a maze of role matrices, permission overrides, and sharing logic nobody can reason about. Here's the concrete migration path from home-grown RBAC to InferaDB — step by step, with a rollback plan.
Google's Zanzibar handles 10 million permission checks per second across every Google product. Every open-source implementation since has hit the same ceiling: general-purpose databases. Here's how Zanzibar works and why InferaDB removes that ceiling.
Authorization is a hidden crisis in modern software. We helped build OpenFGA and saw the architectural limits firsthand. InferaDB is what we wished existed — purpose-built authorization infrastructure, delivered as a managed service.
Traditional authorization handles 1-2 checks per request. AI agent workflows need dozens — and at 5-50ms each, that's seconds of latency before any work happens. The agent era needs authorization infrastructure built for machine-speed decisions.
Authorization checks through general-purpose databases take 5-50ms. InferaDB's purpose-built storage engine delivers 2.8 microsecond p99 reads. Here's the architecture that makes it possible.
If Alice revokes Bob's access at 10:00:00 and Bob's request at 10:00:01 hits a stale replica, he retains access. This is the 'new enemy problem.' InferaDB uses Raft consensus with revision tokens to solve it.
Not everything fits into declarative rules. IP geofencing, subscription tier checks, time-window restrictions — these need real code. InferaDB lets you write that logic in any language, compile to WebAssembly, and run it inside the authorization engine with full sandboxing.
Most teams stitch together RBAC, ReBAC, and ABAC with application code. IPL unifies all three in a single declarative language — statically analyzed at deploy time, evaluated in parallel at query time. One schema, one evaluation, one audit trail.
The fine-grained authorization market is $3.32B and growing at 19.3% CAGR — significantly outpacing the broader IAM market. Yet total VC investment is modest, there's no dominant player, and the category leader position is wide open.
NIS2, DORA, and the EU AI Act all mandate fine-grained, auditable access control — with enforcement deadlines already passing. Here's what each regulation requires and why most authorization systems can't deliver it.
An authorization service has a brutal performance contract: sub-microsecond reads, zero latency spikes, memory safety without compromise. We evaluated Go, Java, and C# seriously. Here's why Rust was the only language that met all three requirements.
Every multi-tenant authorization system promises tenant isolation. Most enforce it with WHERE clauses. One missing filter and data leaks across tenant boundaries. InferaDB enforces isolation with cryptography — cross-tenant access isn't prevented, it's architecturally impossible.
Your RAG pipeline has a security hole. When an LLM retrieves documents to answer a question, it pulls everything the vector search returns — including documents the requesting user shouldn't see. InferaDB enforces per-user authorization before retrieval, not after.
