Weaviate
Vector database software
Database software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
Take the quiz to check if Weaviate and its alternatives fit your requirements.
$45 per month
Free Trial
Free version unavailable
Small
Medium
Large
- Education and training
- Real estate and property management
- Professional services (engineering, legal, consulting, etc.)
What is Weaviate
Weaviate is an open-source vector database used to store and search embeddings for semantic search, retrieval-augmented generation (RAG), recommendation, and similarity matching. It targets software teams building AI-enabled applications that need low-latency vector and hybrid (vector + keyword) retrieval via APIs. The product includes schema-based data modeling, filtering, and integrations for generating or importing embeddings, and it can run self-managed or as a managed cloud service.
Native vector and hybrid search
Weaviate is designed around vector indexing and similarity search, with support for combining vector relevance with keyword-based retrieval. It supports structured filters alongside vector search, which helps teams narrow results by metadata without a separate database. This aligns well with common RAG pipelines where both semantic similarity and constraints (e.g., tenant, document type, time range) matter.
Flexible deployment options
Weaviate is available as open source for self-hosted deployments and as a managed cloud offering. This gives teams a path from local development to production without changing APIs. It also supports containerized deployment patterns that fit common Kubernetes-based operations.
Developer-friendly APIs and tooling
Weaviate exposes APIs that are commonly used by application developers building search and AI features. It provides a schema model for organizing objects and properties, which can simplify application integration compared with purely schemaless stores. The ecosystem includes client libraries and integrations that reduce the amount of glue code needed to connect embedding generation and retrieval.
Not a general-purpose OLTP database
Weaviate focuses on vector and hybrid retrieval rather than full relational transaction processing. Teams often still need a separate system for core application data, complex joins, and multi-statement transactional workflows. Using it as the primary system of record can introduce gaps in constraints and transactional semantics compared with general-purpose databases.
Operational tuning for scale
As data volume and query concurrency grow, teams may need to tune indexing, memory, and sharding/replication settings to maintain performance. Capacity planning can be less straightforward than with traditional keyword search engines or SQL databases because vector index behavior depends on embedding dimensionality and recall/latency targets. Self-managed deployments may require specialized operational knowledge to troubleshoot performance regressions.
Ecosystem and feature trade-offs
Some organizations may find fewer mature enterprise features (e.g., broad SQL compatibility, extensive BI tooling integration, or deep observability integrations) than in long-established database platforms. Hybrid search quality and filtering behavior can require careful evaluation for specific workloads and languages. Teams may need additional components for ingestion pipelines, governance, and end-to-end search analytics depending on requirements.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Free Trial | Free 14‑day trial | Sandbox cluster with Weaviate core DB toolkit (hybrid search, dynamic index, compression, multi-tenancy); baseline RBAC; community support. Pricing dimensions shown on site for this column: Vector dimensions from $0.01668 / 1M, Storage from $0.255 / GiB, Backups from $0.0264 / GiB; Data transfer promotional free. |
| Flex | Starts at $45 /mo (pay-as-you-go, monthly, no-commit) | Shared cloud cluster; pay‑as‑you‑go scaling; 99.5% availability; email support, next-business-day Severity 1 response. Pricing dimensions: Vector dimensions from $0.0139 / 1M, Storage from $0.2125 / GiB, Backups from $0.022 / GiB. |
| Premium | Starts at $400 /mo (prepaid commitment) — contact sales for larger deployments | Shared or dedicated deployment options, up to 99.95% uptime; enterprise support (as low as 1-hour Severity 1 response), SSO/SAML, HIPAA support on Enterprise Cloud, metrics endpoint. Pricing dimensions: Vector dimensions from $0.00975 / 1M, Storage from $0.31875 / GiB, Backups from $0.033 / GiB. |
Additional official add-ons (excerpted from vendor site):
- Weaviate Embeddings (hosted models): e.g., SNOWFLAKE ARCTIC-EMBED-M-V1.5 $0.025 / 1M tokens; ARCTIC-EMBED-M-V2.0 $0.040 / 1M tokens; MODERNVBERT $0.065 / 1M tokens.
- Weaviate Query Agent: Free to try; Monthly plan $30 / organization (includes 4,000 requests) + usage-based pricing for additional requests.
Notes: Pricing page lists a per-plan "Minimum" (Free / $45 / $400) and states high-availability (HA) clusters multiply minimum and usage charges by three; data transfer currently free for a promotional period. For full, region/index/compression-specific rates the site directs users to the Weaviate Cloud Console or to contact support/sales.
Seller details
Weaviate B.V.
Amsterdam, Netherlands
2019
Private
https://weaviate.io/
https://x.com/weaviate_io
https://www.linkedin.com/company/weaviate/
