Zilliz pricing guide details
Pricing Overview
Zilliz Cloud presents pricing plans for managed vector database workloads. The Free tier is listed at $0 and includes 5 GB of storage, 2.5M vCUs per month, and up to five collections. Standard is listed from $0/month for Serverless and from $126/GB/month for Dedicated. Enterprise Dedicated is listed from $197/month and includes a 99.95% uptime SLA, audit logs, SSO, granular RBAC, multi-replica and elastic scaling, and private endpoint and VPC peering.
Business Critical is presented for regulated, mission-critical workloads, but the supplied evidence does not list a public price for that plan. It identifies features including a global cluster, disaster recovery, CMEK, HIPAA eligibility, enhanced data privacy features, and rapid incident response. The pricing page also describes on-demand compute as charging only for active job runtime, with no always-on compute.
For Dedicated workloads, Zilliz lists starting rates from $63 per million vectors per month for performance-optimized clusters, $16 per million vectors per month for capacity-optimized clusters, and $5 per million vectors per month for tiered-storage clusters. These capacity figures are based on evaluations of 768-dimensional vectors. Buyers should confirm their selected plan, cluster type, usage, and actual estimated cost with the calculator or a proof of concept; the evidence says calculator estimates may differ from actual costs.
Plan Comparison
Zilliz Cloud offers four main tiers, each targeting a different stage of the AI development lifecycle. The table below summarizes the key differences.
| Feature | Free | Standard | Enterprise | Business Critical |
|---|---|---|---|---|
| Monthly Price | $0 | From $0 (Serverless) / $99 (Dedicated) | From $155 (Dedicated) | Custom quote |
| Storage Included | 5 GB | Pay-as-you-go | Pay-as-you-go | Pay-as-you-go |
| vCUs Included | 2.5M/month | Usage-based ($4/M vCUs) | Usage-based ($4/M vCUs) | Usage-based |
| Collections | Up to 5 | Up to 100 (Serverless) | Unlimited | Unlimited |
| Uptime SLA | None | None | 99.95% | 99.99% |
| Cloud Providers | Google Cloud | AWS, Google Cloud | AWS, Google Cloud, Azure | All major clouds |
| Security | Basic encryption | Encryption in transit and at rest | SSO (SAML 2.0), granular RBAC, audit logs | CMEK, full-path encryption, HIPAA-eligible |
| Support | Community | Standard | Enterprise support included | Priority support with rapid incident response |
| Networking | Shared | Shared | Private endpoint, VPC peering | Private endpoint, VPC peering |
| Scaling | Fixed | Auto-scaling (Serverless) | Multi-replica, elastic scaling | Global cluster with disaster recovery |
The Free tier works well for learning and prototyping with up to 5 collections on Google Cloud. Standard opens up multi-cloud deployment and offers both serverless and dedicated compute options, with a 30-day free trial for dedicated clusters. Enterprise is a popular tier for production AI applications, delivering private networking and a 99.95% uptime SLA. Business Critical targets regulated industries like healthcare, finance, and government with HIPAA eligibility and a 99.99% uptime SLA.
Hidden Costs and Considerations
The biggest cost variable with Zilliz is vCU consumption. Both read and write operations consume vCUs, and heavy indexing or re-indexing workloads can spike usage unexpectedly. Data egress fees apply when moving vectors between cloud regions or providers. Storage costs for historical or rarely accessed vectors accumulate without proper data lifecycle management. We recommend monitoring vCU usage closely during the first month on a serverless plan, since workloads with unpredictable traffic patterns can produce billing surprises. Index rebuild operations during schema changes also generate substantial compute charges that are easy to overlook.
Cost Estimates by Team Size
The supplied pricing evidence does not provide cost estimates by team size, query volume, or storage footprint, so a reliable monthly estimate for a solo developer, small team, or production team cannot be calculated from it.
Zilliz Cloud lists a Free tier at $0 with 5 GB of storage, 2.5M vCUs per month included, and up to five collections. For Standard, the listed entry points are from $0/month for Serverless and from $126/GB/month for Dedicated. Enterprise Dedicated starts from $197/month and includes a 99.95% uptime SLA, audit logs, SSO, granular RBAC, multi-replica and elastic scaling, and private endpoint and VPC peering.
Buyers should use the cost calculator or evaluate a proof of concept with the listed $200 free credits to validate cost and performance for their own workload. The evidence also states that estimates may differ from actual costs; it does not disclose the usage assumptions needed to turn the listed plan entry points into a team-size total.
How Zilliz Pricing Compares
The supplied evidence provides Zilliz Cloud pricing information only, so it cannot support a like-for-like comparison with Pinecone, ChromaDB, Qdrant, or another vector database.
| Zilliz Cloud plan | Disclosed entry point | Intended use |
|---|---|---|
| Free | $0 | Learning and personal projects; includes 5 GB of storage, 2.5M vCUs per month, and up to five collections |
| Standard | From $0/month (Serverless); from $126/GB/month (Dedicated) | Prototypes, testing environments, and non-critical workloads |
| Enterprise | From $197/month (Dedicated) | Production applications requiring enterprise-grade reliability and controls |
| Business Critical | No public price is listed in the supplied evidence | Healthcare, finance, and other highly regulated, mission-critical systems |
For a meaningful comparison, buyers need comparable official information for each alternative's billing unit, included usage, deployment model, and production-support or security features. Zilliz's displayed pricing also includes Dedicated cluster types with entry points from $63 per million vectors per month for performance-optimized, $16 per million vectors per month for capacity-optimized, and $5 per million vectors per month for tiered-storage workloads.