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<div style="text-align: center;"><img src="assets/img/logo.svg" alt="Oxibase Logo" style="max-width: 200px; height: auto;"></div>
Oxibase is a relation database operating system (DBOS) that provides full ACID transactions with MVCC, a sophisticated cost-based query optimizer.
- **Multiple Index Types**: B-tree, Hash, and Bitmap indexes with automatic type selection
- **Multi-Column Indexes**: Composite indexes for complex query patterns
- **Parallel Query Execution**: Automatic parallelization using Rayon for large datasets
- **Cost-Based Optimizer**: PostgreSQL-style optimizer with adaptive execution and cardinality feedback
- **Semantic Query Caching**: Intelligent result caching with predicate subsumption
- **Disk Persistence**: WAL and snapshots with crash recovery
- **Rich SQL Support**: Window functions, CTEs (including recursive), subqueries, ROLLUP/CUBE, and 101+ built-in functions
## Roadmap Overview
Oxibase is evolving into a distributed, autonomous database system that bridges embedded logic with global resilience. The roadmap outlines the journey from a single-node, scriptable database to a self-managing, AI-enhanced platform.
**Phase 1: Foundation** - Establishing core capabilities through parallel efforts: embedded scripting languages for stored functions and triggers, declarative schema migrations, TUI manager, web server exposure for REST/GraphQL, Postgres wire protocol server, deterministic simulator, and unikernel compilation. These prepare for horizontal scaling.
**Phase 2: Single Node Efficiency** - Unifying operational needs into Oxibase itself with self-monitoring, multiple storage backends, data lifecycle management, and separation of compute & storage.
**Phase 3: Distributed System** - Achieving infinite horizontal scale and global resilience through multi-master consensus, data rebalancing/sharding, geo-sharding, and gossip protocols.
**Phase 4: The Autonomous Cloud** - The database manages its own physical existence and evolves into an AI platform with autonomous networking, auto-infrastructure management, in-database ML inference, and GPU training.
_Figure 1: Phase 1 Dependency Flow_
```mermaid
graph TD;
A[Embedded Scripting Languages<br/>Stored functions & triggers<br/>FaaS-like with debugger] --> B[Web Server Exposure<br/>REST/GraphQL endpoints<br/>DML routes, HTML/function execution]
A --> C[Postgres Wire Protocol Server<br/>Third-party connectivity<br/>Remote control & vertical scaling]
A --> D[Deterministic Simulator<br/>Failure simulation<br/>Horizontal scaling prep]
B --> E[Horizontal Scaling<br/>Post-simulator implementation]
C --> E
D --> E
F[Unikernel Compilation<br/>OS-free, bootable images] --> E
```
For detailed information about each phase, see the [full roadmap](getting-started/roadmap).
## Need Help?
If you can't find what you're looking for in the documentation, you can:
- [Open an issue](https://github.com/oxibase/oxibase/issues) on GitHub
- [Join the discussions](https://github.com/oxibase/oxibase/discussions) to ask questions
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This documentation is under active development. Contributions are welcome!