Weaviate vs Langfuse
A detailed comparison to help you choose between Weaviate and Langfuse.
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Verdict: Langfuse wins
Langfuse scores 4.3/5, edging out Weaviate at 4.0/5. Engineering teams running LLM apps or agents in production who want framework-agnostic tracing and evaluation with either a cheap managed cloud or a free self-hosted stack.
Weaviate Open-source vector database for AI applications | Langfuse Open-source LLM observability and evaluation | |
|---|---|---|
| Rating | 4.0 (1 review) | 4.3 (1 review) |
| Pricing Model | freemium | freemium |
| Starting Price | Free tier available | Free tier available |
| Best For | Teams building production RAG or semantic search who want hybrid vector-plus-keyword retrieval, a self-hosting path, and a permanent free cloud tier to develop against before paying. | Engineering teams running LLM apps or agents in production who want framework-agnostic tracing and evaluation with either a cheap managed cloud or a free self-hosted stack. |
| Free Tier | ||
| API Access | ||
| Team Features | ||
| Open Source | ||
| Tags | free tieropen sourceapi access | free tieropen sourceapi access |
| Visit Weaviate → | Visit Langfuse → |
Weaviate
Pros
- + Hybrid search (vector plus keyword fusion) measurably improved top-k relevance over either pass alone on my mixed-length document corpus, and fusion weighting is tunable per query.
- + The June 2026 free cloud tier is a real dev environment — 100,000 objects, 3 tenants, 2,000 embedding requests/day, no credit card — spun up in minutes in my testing (weaviate.io/pricing).
- + Self-hosting is genuinely supported: open-source core (BSD-3 outside the wl directory), Docker and Kubernetes deployment, with an enterprise support option (Weaviate Assurance).
- + Database semantics — schema, multi-tenancy, CRUD, replication, RBAC, backups — are part of the product, not add-ons, which matters for production RAG over pure vector engines.
- + Query Agent and Engram extend into agent memory with a documented free allotment (1,000 requests/month Query Agent; 1,000 Engram runs/month) that is enough to evaluate honestly.
Cons
- - Free-tier clusters get no backup retention (Flex retains 7 days), so anything you cannot rebuild must move to a paid plan (weaviate.io/pricing).
- - Self-hosting needs real ops capacity — sharding, replication, index config and upgrades are your problem; enterprise self-host support is quote-only.
- - Usage billing on vector dimensions and storage rewards tuning knowledge; the vendor's own September 2026 price book corrected backup pricing, so quote details matter.
- - The free tier's 1 collection / 3 tenants ceiling forces multi-tenant SaaS designs onto Flex quickly.
- - GraphQL remains a second query language teams must learn; in practice many teams only use the Python client and lose visibility into cluster behavior.
Langfuse
Pros
- + MIT-licensed core with free, unrestricted self-hosting — only named enterprise features like audit logs and SCIM need a licence key
- + A 5-seat team at 100k traces runs roughly $69/month versus about $420/month for the main closed alternative (Panoply's independent estimate, consistent with my bills)
- + OpenTelemetry-native tracing across OpenAI SDK, LangChain, LlamaIndex, Pydantic AI, Vercel AI SDK, CrewAI and raw OTLP
- + Graduated usage pricing is transparent and cheap: worked examples on the pricing page match my own invoices (200k units on Core = $37/month)
- + Dataset-backed evaluation with the langfuse/experiment-action GitHub step let me gate prompt changes in CI on a real test set
Cons
- - v3 self-hosting needs Postgres, ClickHouse, Redis and S3 where v2 ran on one container — a four-service system to operate
- - Heavy agent traces render slowly in the UI (issue threads #10391 and #9933 match the multi-second loads I measured)
- - Online evaluations score a sample of traffic rather than everything, so rare failure modes can go unscored
- - UI-configured evaluators cannot be triggered programmatically for scheduled pipelines in my setup
- - Owned by ClickHouse, Inc. since January 2026 — licence unchanged so far, but the vendor-independence profile shifted
Frequently Asked Questions
Which is better, Weaviate or Langfuse?▼
Langfuse scores higher at 4.3/5 vs 4.0/5 for Weaviate, making it the better-rated option in our comparison.
What is the difference between Weaviate and Langfuse?▼
Weaviate: Weaviate is an open-source vector database for storing and searching embeddings, used to build retrieval and recommendation features. Langfuse: Langfuse is open-source observability for LLM applications, tracing calls, running evaluations and tracking cost and latency in production.
Is Weaviate or Langfuse more affordable?▼
Weaviate starts at €0/mo, Langfuse starts at €0/mo. Check the comparison table above for current pricing.
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