Weaviate
Open-source vector DB with hybrid search, now backed by $200M
Overview
Weaviate is an open-source, AI-native vector database that combines vector similarity search with keyword filtering and reranking in one query. Self-host the BSD-licensed core or run it on Weaviate Cloud; raised a $50M Series C at a $200M valuation in October 2025.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 11 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
- 100,000 objects, 1GB memory, 10GB disk
- 1 collection, up to 3 tenants
- 2,000 embedding requests/day
- Unlimited objects, up to 1,000 collections
- 99.5% uptime SLA
- Baseline RBAC security
- Standard next-business-day support
- Up to 99.95% uptime
- SSO/SAML, encrypted volumes, HIPAA (AWS)
- ~40 regions across AWS/GCP/Azure
- 4-hour critical response, dedicated TAM
Use cases
What you can produce with Weaviate
- Hybrid search (BM25 + vector) in a single query
- Built-in vectorizer modules for OpenAI, Cohere, HuggingFace and others
- Self-hosted (BSD-3-Clause) or managed Weaviate Cloud
- Client SDKs for Python, JS/TS, Go and Java
- RBAC and SSO/SAML on the Premium tier
- Multi-tenancy support (collections with tenants)
ASEAN Perspective
Weaviate in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
Weaviate pairs vector similarity with BM25 keyword search in a single query object, and built-in vectorizer modules mean you're not always wiring your own embedding pipeline. G2 reviewers (30+, averaging around 4.6) call out documentation and hybrid search specifically; the same reviewers flag that Weaviate Cloud costs climb fast once your dataset grows and that schema design and sharding have a real learning curve. The October 2025 pricing overhaul replaced the old $25/mo serverless tier with a $45/mo Flex minimum, worth knowing before you budget a pilot. A $50M Series C in October 2025 (Battery Ventures, Index Ventures) at a reported $200M valuation gives it runway against Qdrant, Milvus and Pinecone. Good default for teams that want hybrid search out of the box and don't mind operating it themselves; the BSD-3 license and self-host path keep you off the subscription if you'd rather not pay.
What people say
Weaviate carries roughly 4.6 out of 5 across 30+ reviews on G2, a small but consistently positive sample for the category. Reviewers single out hybrid search — combining BM25 keyword matching with vector similarity in one query — as the feature cited most often, along with client libraries in Python, JS/TS, Go and Java that reviewers describe as smooth to integrate.
Documentation comes up unprompted in multiple reviews as a strength: the getting-started path is short enough that engineers with no prior vector-database experience report shipping a working prototype within a day. Support is also rated well by paying customers, with several reviews noting fast turnaround on technical questions.
The recurring complaint is cost predictability. Weaviate restructured Weaviate Cloud pricing in October 2025, retiring the flat $25/month Serverless tier in favor of a Flex plan that starts at $45/month but is billed on vector dimensions, object storage and backup retention — so the sticker price understates what a production workload with a few million objects actually costs. Reviewers who scaled past the free tier describe having to model usage carefully rather than pick a plan and forget about it. The jump to Premium (from $400/month, prepaid, for dedicated infrastructure and 99.95% uptime) is a big step up from Flex, which some reviewers call an awkward gap for mid-size teams.
The other consistent theme is the learning curve past the basics — schema design, sharding, and choosing the right vectorizer module require reading past the quickstart, which a few reviewers contrast unfavorably with Chroma's simpler local-first API. None of this reads as a dealbreaker in the reviews we found; it's more "budget the ramp-up time," particularly for teams without a dedicated ML infra person.
On GitHub, weaviate/weaviate carries 16.6k stars under a BSD-3-Clause license, and the project ships frequent releases, with the vectorizer module ecosystem (OpenAI, Cohere, HuggingFace and others) expanding alongside the core. The October 2025 Series C ($50M, led by Battery Ventures and Index Ventures, reported $200M valuation) followed a $50M Series B in 2023, putting total disclosed funding around $67.6M — enough runway to keep competing with better-funded rivals like Pinecone without an obvious near-term acquisition or shutdown risk.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including Weaviate's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Weaviate unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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