Pricing Overview
Redis Vector Search pricing follows an enterprise model with a free self-hosted option and usage-based cloud tiers. The core vector search capability ships as part of the Redis Query Engine, available at no cost in the open-source Redis Stack distribution. For managed deployments, Redis Cloud provides the same vector search features with fully hosted infrastructure, starting with a free tier and scaling through fixed and flexible paid plans. The enterprise path requires contacting Redis sales for custom pricing, which bundles dedicated support, SLA guarantees, and advanced deployment options. This structure gives teams a genuine $0 entry point for development and proof-of-concept work, with a clear upgrade path as production demands grow.
Plan Comparison
Redis Vector Search is accessible across multiple Redis deployment options. Here is how they compare:
| Feature | Open Source (Self-Hosted) | Redis Cloud Free | Redis Cloud Essentials | Redis Cloud Pro | Enterprise (Custom) |
|---|---|---|---|---|---|
| Starting Price | $0 | $0 | ~$5/mo | Contact sales | Contact sales |
| Vector Search | Full HNSW + FLAT | Full HNSW + FLAT | Full HNSW + FLAT | Full HNSW + FLAT | Full HNSW + FLAT |
| Hybrid Queries | Yes | Yes | Yes | Yes | Yes |
| Max Database Size | Unlimited (your hardware) | 30 MB | Up to 12 GB | Flexible | Flexible |
| High Availability | Manual setup | No | Basic | Multi-AZ | Multi-AZ + Active-Active |
| Support | Community | Community | Standard | Priority | Dedicated |
| SLA | None | None | 99.9% | 99.99% | 99.999% |
| RBAC & Security | Basic | Basic | Standard | Advanced | Full enterprise suite |
The open-source path works well for teams with in-house Redis expertise who want full control over their infrastructure. Redis Cloud Free provides a quick way to prototype vector search applications without managing servers. Essentials plans suit small production workloads, while Pro and Enterprise tiers deliver the availability and support guarantees that production AI applications require. We recommend starting with the free cloud tier for evaluation, then moving to self-hosted or a paid cloud plan based on your operational preferences and scale requirements.
Hidden Costs and Considerations
Self-hosted Redis Vector Search carries significant infrastructure costs that do not appear in the $0 license price. Vector indexes consume substantial RAM — each 768-dimension float32 vector requires roughly 3 KB of memory, so one million vectors need approximately 3 GB of RAM for the vectors alone, before accounting for metadata and index overhead. HNSW indexes add 20-40% memory overhead on top of raw vector storage. Since Redis runs entirely in memory, your compute costs scale directly with dataset size. Persistence configuration matters too — RDB snapshots and AOF logs require disk I/O that can affect query latency during saves.
On Redis Cloud, bandwidth and data transfer fees apply beyond the base subscription. Cross-region replication and active-active geo-distribution carry additional per-GB charges. Backup storage is included at basic levels but extended retention costs extra. Teams scaling beyond plan limits face automatic upgrades or throttling, depending on configuration. Another consideration is index algorithm choice: HNSW indexes deliver sub-millisecond query latency but consume more memory, while FLAT indexes use less RAM but perform brute-force scans that slow down as dataset size increases. Choosing the wrong algorithm for your workload can either inflate memory costs or degrade query performance at scale.
How Redis Vector Search Pricing Compares
Redis Vector Search competes in a rapidly evolving vector database market. Here is how its pricing stacks up against leading alternatives:
| Tool | Pricing Model | Starting Price | Free Tier | Key Difference |
|---|---|---|---|---|
| Redis Vector Search | Enterprise | $0 (self-hosted) | Yes (Cloud + OSS) | In-memory speed, full Redis data structure access |
| ChromaDB | Usage-Based | $0 | Yes | Purpose-built for embeddings, granular per-resource pricing from $0.09/mo |
| Qdrant | Freemium | $0 | Yes (1 GB free cluster) | Rust-based performance, simple cloud scaling at ~$1/GB |
| Weaviate | Freemium | $45/mo (Flex) | 14-day sandbox | GraphQL-native queries, serverless at $0.055/1M dimensions stored |
Redis Vector Search holds a distinct advantage for teams already running Redis in their stack. Adding vector search to an existing Redis deployment requires no new infrastructure, no additional network hops, and no data synchronization between systems. This architectural simplicity translates to lower total cost of ownership compared to deploying a standalone vector database alongside Redis.
ChromaDB offers the most granular usage-based pricing, making it cost-effective for smaller workloads or teams that want tight cost control per resource. Qdrant delivers competitive cloud pricing with a generous free tier and straightforward per-GB scaling. Weaviate positions itself as the premium managed option with serverless pricing that works well for variable workloads, though its $45/mo Flex minimum is higher than the free entry points offered by Redis, ChromaDB, and Qdrant.
For cost-sensitive teams comfortable with infrastructure management, self-hosted Redis Vector Search paired with Redis Stack is the lowest-cost option at scale — you pay only for compute and memory. For teams prioritizing operational simplicity, Redis Cloud Pro and the managed offerings from Qdrant and Weaviate trade higher per-unit costs for reduced operational burden.