No free plan. The cheapest way in is Open Source at $0 (BSD-3). Consider free alternatives in the vector database category if budget is tight.
Weaviate supports multi-node replication with configurable consistency levels (ONE, QUORUM, ALL) for both reads and writes. The RAFT-based consensus protocol handles leader election and data synchronization across nodes. Built-in backup functionality supports S3, GCS, and filesystem targets. Weaviate Cloud provides managed high-availability with automatic failover and 99.9% uptime SLA.
Yes, Weaviate is fully open-source (BSD-3 license) and designed for self-hosting via Docker or Kubernetes. The official Helm chart supports production Kubernetes deployments with configurable replicas, resource limits, and persistent storage. Weaviate Embedded runs in-process for development and testing. Self-hosted deployments require managing dependencies like the vectorizer modules and configuring HNSW index parameters for optimal performance.
For self-hosted deployments, the main cost driver is memory — HNSW indexes must fit in RAM for optimal query performance. Use product quantization (PQ) to compress vectors and reduce memory requirements by up to 90%. On Weaviate Cloud, costs are based on storage units and compute tiers. Optimize by choosing appropriate vector dimensions, using tenant-based data isolation to avoid over-provisioning, and configuring async indexing for write-heavy workloads.
Weaviate's open-source nature significantly reduces migration risk — you can always run it yourself. The schema-first data model and module-dependent vectorization create some coupling. Mitigate by generating and storing embeddings externally rather than relying on Weaviate's vectorizer modules, using the REST API directly rather than module-specific features, and maintaining export routines via the objects API for data portability.
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Last verified March 2026