CortexDB is a CPU-first, local-first database engine designed for constrained environments.
It is built from scratch as a versioned infrastructure effort, evolving from a minimal LSM-based storage core into a distributed, AI-ready data platform.
CortexDB does not start from hyperscaler assumptions.
It starts from architectural discipline.
The Problem
Most modern data systems are designed with implicit assumptions:
- Abundant RAM
- Always-on cloud connectivity
- GPU availability for vector workloads
- Global distributed consensus
- Hyperscaler-scale infrastructure
These assumptions are not universal.
In many real-world environments, edge deployments, offline-first applications, cost-sensitive infrastructures, emerging data ecosystems, such assumptions introduce fragility, unnecessary complexity, or structural misalignment.
CortexDB explores a different path:
A storage engine that prioritizes:
- CPU efficiency over GPU dependency
- Local autonomy over permanent cloud reliance
- Explicit trade-offs over hidden complexity
- Progressive evolution over premature distribution
Design Philosophy
CortexDB evolves through explicit, versioned architectural steps.
It follows a layered progression:
- V1–V2: Minimal, crash-safe LSM-based storage core
- V3: Query primitives and developer ecosystem
- V4: CPU-first vector search layer
- V5: Replication and offline synchronization
- V6: Advanced CortexQL, secondary indexes, observability
- V7: Pragmatic horizontal sharding without global consensus
Each version defines clear non-objectives.
Complexity is introduced deliberately — never speculatively.
CortexDB does not attempt to become a relational SQL engine.
It does not implement global 2PC or distributed consensus prematurely.
It does not assume infinite hardware.
Instead, it maintains a strict hierarchy:
KV core → JSON documents (optional) → Vector collections → Distributed shards.
Every layer builds on explicit invariants.
Why It Matters
Data infrastructure is becoming strategic.
As AI systems, edge computing, and regional data centers expand, the need for:
- Resource-aware systems
- Predictable performance models
- Controlled operational complexity
- Sovereign infrastructure capabilities
becomes structural.
CortexDB is an exploration of what a modern data engine can look like when:
- CPU is the baseline
- Offline capability is first-class
- Vector search is native
- Distribution is pragmatic, not ideological
It is not a product announcement.
It is a long-term infrastructure effort.