Weaviate hosting
A vector database with hybrid search and built-in vectorization modules.
Weaviate hosting at AIHostBox means a dedicated, single-tenant Weaviate instance on our infrastructure: we install it, pin it to a reviewed release, put it behind TLS on your domain, back it up nightly and keep it patched. Plans start at $11.99 per month and the admin account, the data and any API keys are yours.
Weaviate is an open-source vector database written in Go by Weaviate B.V. and released under the BSD-3-Clause licence. It stores your objects and their vectors together, so a single query can filter on properties, rank by semantic similarity and blend in BM25 keyword scores. That hybrid search, tunable with a single alpha parameter, is its best-known feature, and the reason teams pick it when pure vector search keeps missing exact product codes or names.
The second difference is its module system. Rather than embedding documents in your own pipeline, you can enable a vectoriser such as text2vec-openai or text2vec-ollama and let Weaviate create the vectors on import, then use generative modules to answer questions over the results. A database like this is meant to be always on and reachable by every service that writes to it, which is exactly the job a laptop does badly.
Weaviate hosting plans
Every plan is a dedicated single-tenant instance with NVMe storage, nightly off-box backups, TLS and managed patching. Quarterly, semi-annual and annual terms are discounted at checkout. Model tokens are not included — you bring your own key.
How we run Weaviate
We run a single Weaviate node from the official cr.weaviate.io image, exposing REST and GraphQL on port 8080 and gRPC on 50051, with PERSISTENCE_DATA_PATH on NVMe storage; there is no separate database, as Weaviate stores objects, vectors and indexes itself.
What we configure for you
- AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED=false and API keys via AUTHENTICATION_APIKEY_ALLOWED_KEYS
- AUTHORIZATION_ENABLE_RBAC with a root user, if you want per-key roles
- ENABLE_MODULES and DEFAULT_VECTORIZER_MODULE for the vectoriser you choose
- BACKUP_FILESYSTEM_PATH or BACKUP_S3_BUCKET for Weaviate’s native backup API
- GOMEMLIMIT or LIMIT_RESOURCES so imports slow down instead of running out of memory
- CLUSTER_HOSTNAME fixed, so the node keeps its identity across restarts
Which plan fits
Plus (4 GB) holds roughly 700,000 vectors at 384 dimensions, or about 175,000 at 1,536 dimensions, before quantisation and with room left for the operating system. Pro (8 GB) holds around two and a half times as much and gives headroom for large batch imports. Beyond that, product quantisation or a bigger plan is needed.
The honest limits
This is a single node, so replication across nodes and automatic failover are not part of these plans. Vectoriser modules that run a model locally use the same CPU and RAM as the database, so API-based embeddings are usually the better choice here.
What people run Weaviate for
Search that needs both
Exact keyword matches and semantic similarity in one ranked result.
Ingestion without a pipeline
Let the module embed documents as they arrive.
Per-customer isolation
Use multi-tenancy to keep each customer’s objects in its own shard inside one collection.
Licence and version policy
| Item | Position |
|---|---|
| Upstream licence | BSD-3-Clause |
| Sold as managed hosting | Yes |
| Tenancy | Single tenant — one customer per instance |
| Patching | Critical advisories within 24 hours, high severity within 72 |
Our full position on licences, including the applications we decline to sell, is on the licensing page.
Reading on Weaviate
Works well with Weaviate
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Your private LLM server — pull a model, get an API, keep every token on your own box.
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Dify
A visual studio for building LLM apps, agents and RAG pipelines.
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Qdrant
A fast vector database with real filtering, written in Rust.
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Milvus
Vector search built for very large collections.
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Chroma
A lightweight embedding store that gets out of the way.
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Postgres + pgvector
Vector search inside the database you already trust.
from $5.99/moDetails →Weaviate hosting: your questions
Which client libraries and APIs can I use?
How is access controlled?
How much data fits in memory?
Which vectoriser should I use without a GPU?
How do backups and restores work?
Run Weaviate without running a server
A dedicated Weaviate instance, deployed and maintained by us. Month to month, cancel whenever.