---
title: "Why a Vector Database Alone Won't Cut It (Chroma vs. Our Approach)"
description: "Vector databases like Chroma have exploded in popularity. They solve a very specific problem: finding similar pieces of information fast. But if you mistake a vector DB for a full knowledge substrate, you're going to hit hard limits."
date: "2025-02-24"
publishDate: "2025-02-24T10:00:00.000Z"
author:
  name: "Anthony Rawlins"
  role: "CEO & Founder, CHORUS Services"
tags:
  - "announcement"
  - "contextual-ai"
  - "orchestration"
featured: true
---

**The Chroma Value Proposition**
Chroma is excellent at what it does: store embeddings and return the nearest neighbors. It’s simple, efficient, and useful as a retrieval backend.

**The Limits**
But a database is not a knowledge system. With Chroma, you get:

* Embeddings without meaning — no structured way to represent “where” knowledge lives.
* No sense of time — history is overwritten or bolted on manually.
* No reasoning trail — results come back as raw chunks, not justifications.
* No distributed context — each deployment is its own silo.

**What We’re Doing Differently**
Our stack (Chorus + BZZZ + UCXL) doesn’t replace a vector DB; it **sits above it**.

* We define a protocol for addressing and navigating knowledge, like URLs for context.
* We make time a native dimension, so you can query across versions and histories.
* We attach provenance to every piece of retrieved information.
* And we enable agents — not just apps — to share and evolve context across systems.

**Conclusion**
Chroma is a great building block. But it’s still just a block. If you want to build something more than a single tower — a **city of agents that can collaborate, exchange knowledge, and evolve together** — you need infrastructure that understands time, structure, and justification. That’s the gap we’re closing.