ChromaDB vs. FastEmbed for SaaS RAG

When building a SaaS RAG (Retrieval-Augmented Generation) platform, priorities shift from just “getting embeddings” to:

🚀 Low latency (fast responses)
🔐 Multi-tenancy (firm-level data isolation)
💰 Cost efficiency (handling lots of PDFs without breaking the bank)

Two popular tools come up a lot in this space: ChromaDB and FastEmbed. Let’s see where each fits in your SaaS architecture. Using ChromaDB in SaaS RAG Pros:

Open-source, runs in-process (like SQLite but for vectors).
Great for quick prototyping & small/mid-scale tenants.
Easy to store metadata like tenant_id, product_type, etc.
Can persist to disk or use external backends like Postgres.

Cons:

Single-node by default (limited scaling).
With 100s of firms + millions of chunks, performance may degrade.

✅ Best Fit: Small to medium SaaS deployments where you control infra and want to keep costs low.

Using FastEmbed FastEmbed isn’t a DB — it’s a fast embedding generator. Pros:

Blazing fast embedding generation (optimized for CPU).
No reliance on external APIs (unlike OpenAI) → big cost savings.
Ideal for PDF ingestion pipelines (lots of docs from tenants).

Cons:

Only creates embeddings → you still need a vector DB (Chroma, Qdrant, Pinecone, PGVector).

✅ Best Fit: Embedding pipeline stage in SaaS → compute embeddings locally, then store in Chroma or Qdrant.

Recommended SaaS Setup Here’s how a multi-tenant SaaS RAG stack could look:

Figure: System Flow

PDF Ingestion & Embeddings

from fastembed.embedding import TextEmbedding

# Step 1: Initialize FastEmbed
model = TextEmbedding()

# Step 2: Generate embeddings for chunks
embeddings = model.embed(["Some chunk of text"])

🔹 Store in ChromaDB (per-tenant collection)

import chromadb

# Create persistent DB for tenant firm123
client = chromadb.PersistentClient(path="db/policies_docs")
collection = client.get_or_create_collection("tenant_firm123")

# Add document chunks
collection.add(
    documents=["Requirement text..."],
    embeddings=embeddings,
    metadatas=[{"tenant_id": "firm123", "page": 5}],
    ids=["chunk1"]
)

🔹 Multi-tenant Query Filtering

results = collection.query(
    query_texts=["What are H-1B requirements?"],
    n_results=3,
    where={"tenant_id": "firm123"}  # 🔐 Tenant isolation
)

⚡ Best Practice for SaaS

✅ Use FastEmbed for fast, cheap embeddings.
✅ Use ChromaDB for MVPs or early SaaS (per-tenant collections).
✅ Migrate to Qdrant Cloud / Pinecone once scale increases.
✅ Always filter by tenant_id to prevent cross-firm data leaks.

🎯 Final Takeaway

ChromaDB = lightweight, perfect for MVPs.
FastEmbed = cost-efficient embedding engine.
Qdrant / Pinecone = scale-ready vector DB for production.

👉 For SaaS, the winning combo is:

MVP → ChromaDB + FastEmbed
Scaling → Qdrant + FastEmbed

Read the full article here: https://subhojyoti99.medium.com/chromadb-vs-fastembed-for-saas-rag-4f4b1494bb1c