Documentation

AionDB is a PostgreSQL-wire database engine that keeps relational tables, graph labels, and vector search in one local system. These pages focus on using and evaluating the product. Implementation notes live separately.

Crate-by-crate implementation notes live in Advanced Specification. They are useful for contributors, but they are not the recommended starting point for users evaluating the database.

Choose a path

Status model

AionDB v0.1 is an alpha. The documentation uses conservative language on purpose:

• examples are intended to be runnable;
• unsupported behavior should be stated clearly;
• benchmark claims need reproduction details;
• PostgreSQL compatibility is feature-by-feature;
• graph and vector planning are still evolving.

If a page sounds too broad, prefer the narrower interpretation and validate with a small script.

Start

• Installation: build from source, create a local archive, run the container profile, and review the Kubernetes and systemd templates.
• Getting Started: build the server, create a local user, connect with psql, and run the first query.
• Tutorial: one small dataset using SQL, graph labels, and vector scoring.
• Example Workloads: practical schemas for product, support, and knowledge-base evaluations.

Learn

• Core Concepts: the mental model behind tables, labels, vectors, catalog state, and alpha boundaries.
• Architecture: how the server, engine, catalog, storage, and WAL fit together.
• Query Lifecycle: what happens between a client query and execution.
• Tradeoffs: workloads where AionDB is a good fit, and workloads where it is not.

Build

• SQL, SQL Statements, Data Types, and Functions: the relational surface.
• Graph and Vector, Graph Reference, and Vector Reference: hybrid query features over ordinary tables.
• Indexes and Constraints, Transactions, and System Catalogs: behavior that affects application correctness.
• Interfaces, Client Drivers, PostgreSQL Compatibility, and Ecosystem Integrations: connecting through pgwire, integrating normal SQL tools, or embedding the engine.

Manage

• Configuration: command-line flags, environment variables, and local data directories.
• Administration, Control Plane, Operations, and Security: operating the server during evaluation.
• Observability, Storage Compatibility, Backup and Recovery, and Troubleshooting: diagnosing and recovering local deployments.

Evaluate

• Benchmarks, Benchmark Results, Benchmark Reproducibility, and Performance Tuning: running fair local comparisons and reading visual result snapshots.
• Testing, Evaluation Checklist, Product Hardening Plan, and Migration Guide: deciding whether a workload is ready to try.
• Limitations, Error Reference, FAQ, and Glossary: boundaries and terminology.

Project

• Roadmap, Governance, GTM Evidence, Release Notes, and Release Process: where the project is going, how decisions are made, what evidence supports claims, and how releases are described.
• Contributing: how to work on the codebase without starting from crate-level internals.

Reading order for reviewers

For a fast technical review, read:

1. Core Concepts
2. Tradeoffs
3. Limitations
4. PostgreSQL Compatibility
5. Benchmarks

That path answers the main credibility questions before going deep into reference pages.