Weaviate Cloud

docs.weaviate.io ↗

Provision a managed Weaviate vector database and build collections for similarity search and retrieval workflows.

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Screenshot of the Weaviate Cloud homepage

What it does

Weaviate Cloud is a managed vector database service. Its console provisions clusters while the database stores objects and vectors for similarity search, retrieval-augmented generation (RAG), and related application queries. The Cloud quick start creates a collection, imports data, runs a vector search, and can continue to a RAG example. Users can start with a free cluster and move to paid shared or dedicated options when their workload outgrows the free limits.

Create a collection and query its data

The official Weaviate Cloud quick start walks through setting up a cluster, creating a collection, importing data, and running a similarity search. It also demonstrates a RAG flow and Query Agent, with model integrations where enabled. A useful first task is to load a small set of documents, decide whether the collection should use a Weaviate Embeddings integration or vectors created elsewhere, then test queries against the returned objects. These steps describe the documented workflow; no account, cluster, or query was created for this record.

Weaviate Cloud manages the database infrastructure, but the application still has to select the collection schema, supply data, and decide which embedding or generative-model services it will use. A free cluster is limited to one cluster per user with published object, memory, disk, and collection caps. Shared Cloud clusters are usage-based, and embeddings or generative model features can add separate usage charges. The pricing page distinguishes these options; exact costs depend on configuration and use.

A user account is required to manage clusters in the Cloud console, while the free cluster does not require a billing account or credit card. This entry covers the hosted Weaviate Cloud service, not self-managed Weaviate software.

Strengths

  • The quick start shows collection creation, data import, vector similarity search, and an example RAG workflow.
  • The free cluster is available without a credit card or billing account for learning and small projects.
  • The service offers managed clusters with shared or dedicated paid deployment options.

Watch out for

  • The free cluster has caps on cluster count, objects, memory, disk, collections, and tenants.
  • Managing a cluster requires a user account, and paid cluster or model usage can add costs beyond the free tier.

Best for

  • Prototyping a vector-search or RAG application without operating database infrastructure
  • Teams that want managed Weaviate clusters with a path from a free prototype to paid shared or dedicated capacity

Sources