Comparison

Epsilla vs Faiss

No leader: the top candidate Epsilla has only 0.29 confidence (low), below the 0.35 needed to declare a winner. The attribute-by-attribute breakdown below, with a source and date on every value, is the honest way to compare them.

Machine formatsMarkdownJSONGraphQLMarkdown is open. JSON and GraphQL need a free key.
Epsilla65
Faiss57
Score
vioscaleAI score
Epsilla65 / 100low · 29%
Faiss57 / 100low · 35%
Pricing
Free tier
Epsilla✓
Faiss–
Model
Epsillafreemium
Price level
Epsillamid
Faissfree
Transparent
Epsilla✓
Faiss–
Reliability
Sla pct
Epsilla99.9
Faiss–
Status page
Epsilla✓
Faiss✓
Adoption
Dependent repos
Epsilla–
Faiss5,592
Github stars
Epsilla–
Faiss41,146
Activity
Commits last 30d
Epsilla–
Faiss66
Release
Cadence days
Epsilla–
Faiss83
History
Epsilla–
License
Spdx
Epsilla–
FaissMIT
Language
Primary
Epsilla–
FaissC++
Content
Faq
Epsilla4 items
Faiss5 items

Capabilities

Feature-by-feature on the axes that matter for vector databases. “-” means undocumented, not absent.

Deployment
Deployment
EpsillaManaged
FaissSelf-hosted
Serverless / consumption pricing
Epsilla✓
Faiss✗
Index
ANN index (HNSW / IVF / DiskANN / ScaNN / flat)
Epsilla-
FaissHNSW, IVF, PQ, multi-index, NSG
Distance metrics (cosine / dot / Euclidean)
Epsilla-
FaissEuclidean (L2), inner product, L1, Linf
Query
Metadata filtering
Epsilla-
Faiss-
Hybrid search (dense + sparse fusion)
Epsilla-
Faiss-
Built-in BM25 / lexical
Epsilla-
Faiss-
Storage
Quantization
Epsilla-
FaissProduct
On-disk vs in-memory
Epsilla-
FaissDisk-backed
Scale
Multi-tenancy (namespaces / collections / tenants)
Epsilla✓
Faiss-
Horizontal scale
Epsilla-
FaissSingle-node
Consistency
Consistency
Epsilla-
Faiss-
Licensing
Licence class
EpsillaProprietary
FaissPermissive OSS
Classification
Purpose-built vs feature-of-parent
EpsillaFeature of parent
FaissExtension

What each one is

The product in its own terms, so the numbers below have context.

Epsilla

A platform that enables teams to build and deploy AI applications by combining language models with searchable knowledge repositories. It simplifies the setup and management of retrieval-augmented generation workflows without requiring technical engineering.

Independently observed

Faiss

Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM.

Independently observed

Pricing

List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.

Epsilla

from $29/moSubscriptionFree tier

Free tier through $2,499/month. Custom pricing for Enterprise. Metered add-ons $2–39/month.

  • Free TierFree
    • 1 Team Member
    • 1 Project
    • 1 AI Application
    • 1 Knowledge Base
    • 10M Vector Storage
    • +3 more
  • Starter Tier$29/month
    • 2 Team Members
    • 1 Project
    • 5 AI Applications
    • 5 Knowledge Bases
    • 1G Vector Storage
    • +2 more
  • Professional Tier$249/month
    • 20 Team Members
    • 10 Projects
    • 50 AI Applications
    • 50 Knowledge Bases
    • 10G Vector Storage
    • +3 more
  • AI Concierge$2,499/month
    • Everything in Professional
    • Fractional Forward Deployed AI Engineer
    • Done-For-You AI Agent & Workflow Build-Out
    • Domain-to-AI Enablement
    • Weekly Strategy & Review Calls
    • +3 more
  • Enterprise TierContact sales
    • Unlimited Team Members
    • Unlimited Projects
    • Unlimited AI Applications
    • Unlimited Knowledge Bases
    • Unlimited Vector Storage
    • +6 more
as of verify ↗

Faiss

Open source
as of verify ↗

Platform & deployment

Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.

Platforms
Web
Epsilla✓
Faiss✗
macOS
Epsilla✗
Faiss✓
Windows
Epsilla✗
Faiss✓
Linux
Epsilla✗
Faiss✓
Deployment
Cloud / SaaS
Epsilla✓
Faiss✗
Self-hosted
Epsilla✓
Faiss✓
On-premise
Epsilla✓
Faiss✗
Still deciding?

Epsilla or Faiss: which one depends on you

A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.

Free to run, no account needed to start. How the evaluation works

Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.