Make Powerful Database Capabilities
Accessible to Every Developer

We believe that modern applications shouldn't need separate databases for transactions, analytics, and AI. HeliosDB brings these capabilities together in a single, easy-to-use package that requires no operational expertise.

The Problem We Solve

Modern applications have complex data needs spanning transactions, analytics, and AI.

Traditional Approach

3 Databases Required
┌─────────────┐   ┌─────────────┐   ┌─────────────┐
│ PostgreSQL  │   │ ClickHouse  │   │  Pinecone   │
│   (OLTP)    │   │   (OLAP)    │   │  (Vectors)  │
└─────────────┘   └─────────────┘   └─────────────┘
       ▲                 ▲                 ▲
       └─────────────────┴─────────────────┘
                  Complex Sync
                  Multiple Teams
                  Higher Costs

Transaction Processing (OLTP) — User data, orders, sessions. ACID guarantees required. Low-latency reads and writes.

Analytics (OLAP) — Business intelligence, aggregations and reporting, time-series analysis.

AI & Vector Search — Semantic search, recommendation systems, RAG pipelines.

HeliosDB Solution

1 Unified Database
┌───────────────────────────────┐
│           HeliosDB              │
│  OLTP + OLAP + Vector Search    │
│  Single Database, Zero Config   │
└───────────────────────────────┘
Single deployment

No complex sync between databases

One team to manage

Reduced operational overhead

Lower costs

Pay for one database, not three

Born From Frustration

We were building AI applications and found ourselves managing three or four different databases—PostgreSQL for user data, Redis for caching, Pinecone for vectors, and ClickHouse for analytics. Each had its own operational overhead, sync logic, and failure modes.

We asked: Why can't one database handle all of this?

So we built one.

Starting with a Rust-based storage engine on RocksDB, we added PostgreSQL wire protocol compatibility, native HNSW vector indexing, columnar storage for analytics, and unique features like database branching and time-travel queries. The result is a database that's as simple to deploy as SQLite but as powerful as a full data platform.

Core Values

Simplicity First

Zero configuration should be the default. Advanced options for those who need them, but batteries included for everyone else.

Developer Experience

Developers shouldn't need to be database experts. Clear documentation, helpful error messages, and predictable behavior.

Open Source

The core database is Apache 2.0. We believe in transparency and community. Enterprise features fund continued development.

Performance Without Sacrifice

Fast shouldn't mean fragile. We optimize aggressively but never at the cost of data integrity.

AI-Native

AI applications have unique needs—vector search, semantic caching, embedding storage. We build for this future.

Built With the Best Technology

Rust

Memory safety, performance, fearless concurrency

RocksDB

Battle-tested LSM-tree storage engine

Apache Arrow

Columnar format for analytics

HNSW

State-of-the-art approximate nearest neighbor search

PostgreSQL Wire Protocol

Compatibility with existing tools and ORMs

Proudly Open Source

HeliosDB is open source under the Apache 2.0 license. Contributions are welcome.

Trust

You can audit every line of code storing your data

Longevity

The project outlives any company

Community

Better software through collaboration

Adoption

Lower barrier to try and adopt

View on GitHub →

Meet the Team

We're a team of database engineers, systems programmers, and developer advocates united by a passion for great developer tools.

DM

Daniel Moya

Founder & CTO

Database Architecture & Distributed Systems

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VP Engineering

Distributed Systems

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Head of DevRel

Community & Advocacy

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