Onyx Database AI-Controlled Database Cloud Services

Structured data, made flexible and intelligent.

An API-driven database management system with a built-in AI control plane for planning, generating, and managing repeatable data workflows across connected data—with humans in the loop.

workflow.ts
1. Save & Query
const widget = { 
  name: "M2-55",
  category: "Electronics",
  description: "A powerful gadget..."
}

await db.save(tables.Product, widget);

const results = await db.from(tables.Product)
  .search("gadget AND powerful")
  .and("category", "Electronics")
  .list();
2. Natural Language AI
const answer = await db.chat("what is a M2-55?");

What Is Onyx?

A faster approach at developing web applications

Onyx Cloud is an API-driven database management system and AI agentic control plane with built-in RAG (Retrieval Augmented Generation) capabilities for querying data across structured tables (using rest api and client sdk builder pattern constructed queries) and unstructured documents (inverted index searching). It automatically generates optimized queries for structured data and enables natural-language access across your entire data model. Onyx can be used to atomically save data, with extremely fast read and write performance, as well as resolve flexible relationships to other graphs.

Built for Evolving Teams

Onyx is designed for systems where data is:

  • Highly connected
  • Constantly evolving
  • Analyzed continuously

Why Traditional Databases Slow you down

The Old Way

  • • Fixed schemas and rigid relationship constraints
  • • Manually written static queries
  • • Analysis performed outside the DB

The Pitfalls

Approaches like this don't evolve and have limited AI capabilities; the result is less data-driven AI insights.

How Onyx Is Different

Onyx models data as entities in collections, but relationships are not stored as rigid edges.

  • Relationships are still defined at a declarative schema level
  • Resolver queries script retreive connected nodes
  • Graphs attach at the model level
  • Resolution happens inside the DB

Backed by indexed based joining and optimized traversal structures on solid state drives to mitigate N+1 performance issues.

AI Control Plane

Rather than writing one-off SQL, users work with workflow trees that analyze intent, generate queries, and route to dynamic workflows

Every step is traceable. Humans approve all mutations.

First-Class Outputs

  • statistical summaries
  • derived datasets
  • narrative explanations
  • visualization-ready results

How Teams Use Onyx

  • Graph-shaped domain models
  • Analytics over evolving schemas
  • AI and RAG backends
  • Authorization and policy systems
  • Internal data platforms

Why It Matters

Stop inheriting database tradeoffs

SQL forces rigid schemas and join complexity. MongoDB pushes integrity and relationships into application code. Elasticsearch adds ETL pipelines and eventual consistency. BI tools sit on top and require manual grids and charts. Onyx replaces these forced compromises by keeping structure, enabling flexible relationships, and using an AI control plane to generate workflows, queries, visualizations, and narrative insights.

SQL
The tradeoff

Structured, but rigid. Migrations, schema friction, and relationship-heavy queries devolve into join complexity.

What Onyx changes

Keep structure while allowing relationships to evolve without redesigning your schema surface area.

MongoDB
The tradeoff

Easy to start, then inconsistent documents, duplication, and app-level logic become the system of record.

What Onyx changes

Structured data handling designed to be flexible and intelligent—without pushing complexity into application code.

Elasticsearch
The tradeoff

Search is powerful, but usually requires ETL, denormalized indexes, and eventual consistency between systems.

What Onyx changes

Transactional data with Lucene-style fuzzy search in real time—no ETL pipeline, and search stays consistent with live data.

BI Tools
The tradeoff

Dashboards require manual grids and chart configuration, and logic often lives in brittle report definitions.

What Onyx changes

AI assistants generate queries, visualizations, and content-driven insights—so dashboards are built from reusable workflow outputs.

Onyx separates data modeling, relationship definition, and data workflow orchestration, and optimizes each independently. This is what makes AI-directed, trustworthy data workflows possible inside a real database system.

Rethink how database work gets done

Learn how Onyx works, explore the architecture, or dive into the technical model behind resolver-defined relationships and AI-controlled workflows.