Milvus Pricing: Free Open-Source & Managed Cloud Costs (2026)

Pricing overview

Milvus offers a dual pricing model: the open-source Milvus vector database is freely available for self-hosting, incurring only the infrastructure costs of its deployment environment. For users seeking a managed solution, Zilliz Cloud provides Milvus as a service, featuring a free tier and usage-based pricing for compute and storage. This model allows developers to begin with the free tier and scale resources as their application demands grow, paying only for the resources consumed beyond the free limits Zilliz Cloud Pricing. The primary cost drivers for Zilliz Cloud are Compute Units (CUs), which encapsulate processing power, and storage in gigabytes.

The open-source Milvus project, maintained by Zilliz, is distributed under the Apache License 2.0, meaning there are no direct licensing fees for its use Milvus documentation. Organizations deploying open-source Milvus are responsible for managing their own infrastructure, including servers, networking, and maintenance. This can involve costs from cloud providers like AWS, Azure, or Google Cloud, or on-premises hardware and operational overhead. The choice between self-hosting and a managed service often depends on factors such as operational expertise, desired control over the environment, and scalability requirements.

Plans and tiers

Milvus itself is an open-source project and does not have traditional 'plans' or 'tiers' in terms of licensing. Its usage is free, with costs being solely related to the infrastructure it runs on. For instance, deploying Milvus on a cloud provider like AWS EC2 instances or Google Cloud Compute Engine would involve charges for virtual machines, storage, and network egress.

Zilliz Cloud, the managed service for Milvus, offers a more structured set of tiers based on resource consumption. While specific named plans are not explicitly defined, the pricing model is usage-based, characterized by the allocation of Compute Units (CUs) and storage:

• Compute Units (CUs): CUs represent the processing power dedicated to vector search and indexing operations. Zilliz Cloud bills CUs on an hourly basis, starting from $0.09 per CU-hour. The number of CUs required scales with query QPS (queries per second), data indexing speed, and overall data volume.
• Storage: Storage is billed per gigabyte per month, starting from $0.08 per GB-month. This covers the storage of vector embeddings and associated metadata. As the volume of data stored in Milvus increases, so does the storage cost.
• Data Transfer: Ingress data transfer is typically free, while egress data transfer may incur charges, depending on the cloud provider and region.

Users can dynamically adjust the number of CUs and storage capacity through the Zilliz Cloud console to match their application's needs, providing flexibility to scale up during peak loads and scale down to optimize costs during off-peak periods. Zilliz Cloud also offers enterprise-grade features, including advanced security, dedicated resources, and priority support, which are typically customized based on specific organizational requirements and may involve separate agreements Zilliz Cloud service pricing details.

Free tier and limits

The open-source Milvus project, by its nature, functions as a perpetual free tier, limited only by the user's available infrastructure and operational capabilities.

Zilliz Cloud offers a specific free tier designed for developers to experiment with the managed service and build small-scale applications without immediate cost. The Zilliz Cloud free tier includes the following allocations:

• 1 Compute Unit (CU): This provides a baseline level of processing power for vector operations.
• 2 GB of storage: Sufficient for storing a moderate number of vector embeddings and associated metadata.
• 10,000 requests/month: This limit applies to the total number of API calls made to the Milvus instance, crucial for managing query and data insertion rates.

The Zilliz Cloud free tier is intended for development, testing, and small-scale proof-of-concept projects. It allows users to gain familiarity with the managed Milvus environment, test API integrations, and evaluate performance characteristics without incurring charges. Once these limits are exceeded, the account automatically transitions to usage-based billing according to the rates outlined in the 'Plans and tiers' section. Users can monitor their usage through the Zilliz Cloud console to track their consumption against the free tier limits Zilliz Cloud free tier information. This structured approach helps prevent unexpected costs while providing ample resources for initial development.

Real-world cost examples

Understanding real-world costs for Milvus largely depends on whether you opt for the self-managed open-source version or the managed Zilliz Cloud service. For self-managed Milvus, costs are entirely dependent on your infrastructure choices. For Zilliz Cloud, costs are usage-based.

Example Scenarios for Zilliz Cloud:

Scenario 1: Small Development Project

• Purpose: Building a proof-of-concept application or a small internal tool.
• Usage: Stays within the free tier limits for the first few months. Eventually, exceeds limits slightly.
• Resources:
  • Compute: 1.5 CUs (average, going slightly over 1 CU free tier)
  • Storage: 3 GB (average, going slightly over 2 GB free tier)
  • Requests: 15,000 per month (exceeding 10,000 free tier)
• Estimated Monthly Cost:
  • Compute: (1.5 CU - 1 CU free) * $0.09/CU-hour * 730 hours/month = $32.85
  • Storage: (3 GB - 2 GB free) * $0.08/GB-month = $0.08
  • Requests: (15,000 requests - 10,000 free) * $0.00001/request (example rate for excess requests, actual rates may vary for requests beyond free tier) = $0.05
  • Total Estimated: Approximately $33.98/month

Scenario 2: Medium-Scale Production Application

• Purpose: A production application with moderate user traffic, storing a significant number of embeddings for recommendation systems.
• Usage: Consistent daily usage, moderate indexing, regular queries.
• Resources:
  • Compute: 10 CUs
  • Storage: 200 GB
  • Requests: 5,000,000 per month
• Estimated Monthly Cost:
  • Compute: (10 CU - 1 CU free) * $0.09/CU-hour * 730 hours/month = $599.40
  • Storage: (200 GB - 2 GB free) * $0.08/GB-month = $15.84
  • Requests: (5,000,000 requests - 10,000 free) * $0.00001/request = $49.90
  • Total Estimated: Approximately $665.14/month

Scenario 3: Large-Scale Enterprise Solution

• Purpose: High-performance search for millions of items, integrated into critical business applications.
• Usage: High concurrency, frequent data updates, large datasets.
• Resources:
  • Compute: 50 CUs
  • Storage: 2 TB (2000 GB)
  • Requests: 50,000,000 per month
• Estimated Monthly Cost:
  • Compute: (50 CU - 1 CU free) * $0.09/CU-hour * 730 hours/month = $3,227.70
  • Storage: (2000 GB - 2 GB free) * $0.08/GB-month = $159.84
  • Requests: (50,000,000 requests - 10,000 free) * $0.00001/request = $499.90
  • Total Estimated: Approximately $3,887.44/month

These examples illustrate how Zilliz Cloud costs scale with resource consumption. Actual costs may vary based on specific usage patterns, data transfer, and any custom enterprise agreements. It is always recommended to refer to the official Zilliz Cloud pricing page for the most current and detailed information.

How the pricing compares

When evaluating Milvus's pricing, it's important to consider both the open-source self-managed option and the managed Zilliz Cloud service, especially when comparing against other vector databases like Pinecone, Weaviate, and Qdrant. Each alternative offers different pricing models, often with free tiers and usage-based scaling.

Open-Source Milvus vs. Managed Alternatives

The primary appeal of open-source Milvus is its zero licensing cost. Users deploying Milvus on their own infrastructure only pay for the underlying cloud resources (e.g., AWS EC2, S3, EBS, or Google Cloud Compute Engine, Persistent Disk) and operational overhead (staff, maintenance). This can be significantly cheaper for organizations with existing infrastructure and DevOps capabilities, particularly for large-scale deployments where managed service fees might become substantial. However, it requires a higher degree of technical expertise for setup, scaling, and maintenance.

Zilliz Cloud vs. Other Managed Vector Databases

Zilliz Cloud competes directly with other managed vector database services. The pricing models are generally usage-based, focusing on compute, storage, and requests. Here's a comparative overview:

Key Differences in Pricing Models:

• Resource Granularity: Zilliz Cloud's CU model directly ties to compute power. Pinecone uses 'pods' which bundle compute and storage. Qdrant often separates read/write units from storage. Weaviate typically offers instance-based tiers.
• Free Tiers: All major managed vector databases offer free tiers to allow initial development and testing. Zilliz Cloud's free tier is competitive with its allocation of 1 CU and 2 GB storage. Pinecone's Starter plan is notable for not requiring a credit card, facilitating quick trials.
• Scaling Factors: For Zilliz Cloud, scaling primarily involves adjusting CUs and storage. For Pinecone, scaling involves adding more pods or upgrading pod types. Qdrant scales with storage and read/write units. These differences impact how costs accumulate as an application grows.
• Open-Source Option: Milvus (and Weaviate and Qdrant) provide robust open-source versions that can be self-hosted, offering a completely free-of-licensing-cost alternative to their managed services. Pinecone, by contrast, is primarily a managed service with no open-source equivalent. This provides Milvus with a significant advantage for organizations that prefer full control over their data and infrastructure, or have stringent budget constraints for licensing. For those comparing the fully managed service, the specific rates per compute unit, storage, and request become the primary differentiator, which are subject to change and should be verified on the respective providers' pricing pages.

Ultimately, the best choice depends on the specific project's scale, performance requirements, operational budget, and internal technical expertise. Organizations must weigh the cost savings of self-hosting against the convenience, scalability, and managed support of cloud services.