MongoDB Pricing Breakdown: A 2025 Cost Guide

Introduction

In today’s data-driven world, choosing the right database solution goes beyond just selecting a powerful technology—it must also fit into your budget. MongoDB, a highly flexible and scalable NoSQL database, has become a top choice for developers and enterprises alike. Yet, navigating the various pricing models across different cloud providers can be daunting.

In this blog post, we’ll break down the essential considerations for MongoDB pricing, from understanding the technology itself to comparing the most popular providers and exploring free alternatives. By the end, you’ll be equipped with the insight you need to confidently choose the right MongoDB solution for your unique needs.

What Is MongoDB ?

MongoDB is a document-oriented NoSQL database that stores data in flexible JSON-like structures called BSON (Binary JSON). This structure allows dynamic schemas, making MongoDB particularly well-suited for applications requiring real-time analytics, flexible data modeling, and high scalability.

Some of MongoDB’s standout advantages include:

• Flexibility: Instead of rigid tables and columns, you can nest documents and arrays, accommodating evolving data models.
• Horizontal Scalability: MongoDB’s sharding mechanism allows databases to be split across multiple machines, making it easier to scale horizontally.
• Robust Ecosystem: A large community, comprehensive documentation, and a variety of tools and connectors enhance developer productivity.
• Use Cases: MongoDB is often the first choice for real-time analytics, content management systems, mobile and IoT applications, and any project with unstructured or rapidly changing data.

MongoDB Providers

While MongoDB can be self-hosted, managed services have gained traction for their convenience, support, and integrated tooling. Below are some of the major cloud providers offering MongoDB or MongoDB-like database services, each with distinct features and pricing models:

1. MongoDB Atlas
   • Official Managed Service: Backed by the team behind MongoDB itself.
   • Focus on Ease of Use: Automated patching, backups, and a suite of performance monitoring tools.
2. Amazon Web Services (AWS)
   • DocumentDB: Although not an exact 1:1 replica of MongoDB, AWS DocumentDB is compatible with many MongoDB APIs.
   • Integration: Tight ecosystem integration (VPC, IAM, etc.) and robust scaling options.
3. Microsoft Azure
   • Cosmos DB (MongoDB API): Offers wire protocol compatibility with MongoDB, targeting low-latency globally distributed apps.
   • Enterprise Features: Azure’s strong enterprise toolchain appeals to large organizations with pre-existing Azure investments.

Each of these providers offers unique advantages in terms of integrated services, global availability, and enterprise support. The key is understanding how their distinct pricing structures align with your technical requirements.

Pricing Structures by Provider

MongoDB Atlas Pricing

MongoDB offers a flexible and scalable pricing structure, tailored to a wide range of workload requirements. The pricing options are divided into two main categories:

1. Atlas Cloud Platform Plans:
   • Shared Tier Pricing: Ideal for test environments and small-scale applications.
   • Dedicated Cluster Pricing: Suitable for production environments requiring exclusive resources.
   • Serverless Pricing: Designed for applications with unpredictable or spiky workloads.
2. Enterprise Advanced:
   • A separate offering designed for organizations requiring on-premises or private cloud deployments with advanced features, enterprise-grade security, and dedicated support.

Shared Tier Pricing (Part of Atlas Cloud Platform)

MongoDB Atlas’s Shared Tier Pricing is perfect for those starting their journey with MongoDB or running lightweight applications. This pricing plan is available across all three major cloud providers—AWS, Azure, and Google Cloud Platform (GCP)—with consistent pricing, ensuring seamless decision-making when choosing a provider.

Cluster Tiers and Pricing:

M0 (Free Forever):

• Storage: 512 MB
• RAM: Shared
• vCPUs: Shared
• Cost: Free
• Use Case: Ideal for prototyping and personal projects.

M2 ($9/month):

• Storage: 2 GB
• RAM: Shared
• vCPUs: Shared
• Cost: $9/month
• Use Case: Suitable for small workloads or lightweight testing.

M5 ($25/month):

• Storage: 5 GB
• RAM: Shared
• vCPUs: Shared
• Cost: $25/month
• Use Case: Entry-level production applications or slightly larger test environments.

Dedicated Cluster Pricing (Part of Atlas Cloud Platform)

Dedicated Cluster Pricing is designed for production-grade applications that require high performance, scalability, and exclusive resource allocation. These clusters offer flexibility and reliability for businesses of all sizes, backed by MongoDB’s fully managed service.

Key Features of Dedicated Clusters

       1. Exclusive Resources:

Each cluster includes dedicated vCPUs, RAM, and storage, ensuring consistent performance with no shared resource contention.

       2. Multi-Region Availability:

Deploy clusters across multiple regions to enhance global availability and disaster recovery.

       3. Scalability:

Scale up or down based on workload demands with ease.

       4. High Availability:

Automated failover and replication across multiple nodes ensure continuous uptime and data integrity.

Billing Factors

The cost of a dedicated cluster is determined by:

• Cluster Tier: Pricing increases with larger configurations, which include more vCPUs, RAM, and storage.
• Data Transfer: Charges apply for data egress and cross-region replication.
• Backup and Add-ons: Optional features such as continuous backups or advanced encryption incur additional costs.

Pricing Examples

Although prices can vary based on the cloud provider (AWS, Azure, GCP) and region, here are some examples for common cluster sizes:

M10:

• Storage: 10 GB
• RAM: 2 GB
• vCPUs: 2
• Base Price: $0.08/hour

M30:

• Storage: 40 GB
• RAM: 8 GB
• vCPUs: 2
• Base Price: $0.54/hour

M50:

• Storage: 160 GB
• RAM: 32 GB
• vCPUs: 8
• Base Price: $2.00/hour

These are just a few of the available configurations. For a full list of cluster tiers and pricing, visit the MongoDB Atlas Pricing Page.

Use Cases for Dedicated Clusters

1. Enterprise Applications:

Large-scale e-commerce, CRM systems, and ERP applications.

      2. Analytics and Big Data:

High-throughput real-time analytics for data-driven decision-making.

      3.  IoT and Streaming Data:

Handling continuous data streams from connected devices with low-latency processing.

Serverless Pricing (Part of Atlas Cloud Platform)

The Serverless Pricing model is ideal for applications with unpredictable or dynamic workloads. With serverless clusters, you only pay for the operations you run, eliminating the need to provision resources in advance. This flexible model is designed for cost efficiency, as you’re billed based on actual usage rather than reserved capacity.

Key Features of Serverless Clusters

1. Pay-as-You-Go:

Billing is based on read and write operations, storage usage, and backups. No upfront resource allocation is required.

     2. Automatic Scaling:

Resources dynamically adjust to match workload demands, ensuring performance without manual intervention.

     3. Cost Optimization:

Perfect for workloads with spikes or seasonal traffic, where consistent provisioning could lead to overpaying for unused capacity.

Billing Components

1. Read Processing Unit (RPU):
   • Represents the number of read operations and documents scanned per operation.
   • Pricing:
     • $0.10 per million RPUs for the first 50 million/day.
     • Discounted tiers: $0.05/million for the next 500 million reads, and $0.01/million thereafter.
2. Write Processing Unit (WPU):
   • Represents the number of write operations to the database.
   • Pricing: $1.00 per million WPUs.
3. Storage:
   • Charged per GB-month for data and indexes stored on the database.
   • Pricing: $0.25/GB-month.
4. Backups:
   • Two free daily snapshots are included. Additional snapshots or restores are billed.
   • Standard Backup Restore: $2.50/hour.
   • Continuous Backup: Retains backups for up to 35 days at $0.20/GB-month.
5. Data Transfer:
   • Regional Data: $0.01/GB for data transfer within the same region.
   • Cross-Region Data: Ranges from $0.02/GB to $0.20/GB depending on the regions.
   • Public Internet Transfer: Between $0.09/GB and $0.20/GB for transfers to or from the public internet.

Use Cases for Serverless Clusters

1. Startups and New Applications:

Ideal for projects with unpredictable user activity or workloads that fluctuate based on seasonal trends.

     2. Burst Workloads:

Applications experiencing spikes in traffic, such as event ticketing or flash sales, benefit from the dynamic scaling.

     3. Prototyping and Experimentation:

Perfect for developers testing applications with variable query loads.

Enterprise Advanced (Separate from Atlas Cloud Platform)

For organizations with on-premises or private cloud needs, MongoDB offers Enterprise Advanced, a comprehensive solution that goes beyond the Atlas Cloud Platform. This plan is tailored for large enterprises with stringent security, compliance, and operational requirements.

Key Features of Enterprise Advanced:

• MongoDB Enterprise Server: A robust, fully managed database engine.
• Ops Manager: For simplified monitoring, backups, and automation.
• Kubernetes Operator: For containerized MongoDB deployments.
• Enterprise Security Features: Including advanced encryption and auditing.
• Business Intelligence Integration: Tools for analytics and visualization.
• Rich Support: Commercial licenses, consultant support, and regular check-ins.

Note: Pricing for Enterprise Advanced is not publicly listed and requires contacting MongoDB sales for a tailored agreement.

MongoDB Atlas also provides a range of additional services for monitoring, analytics, and developer tools—many of which can be included in your overall pricing depending on usage. You can explore these offerings directly on the MongoDB Atlas platform. These are just a few of the available configurations. For a full list of cluster tiers and pricing, visit the MongoDB Atlas Pricing Page.

AWS (Amazon DocumentDB) Pricing

Amazon DocumentDB (with MongoDB compatibility) is a fully managed document database designed with flexible, pay-as-you-go pricing. Its pricing model is built to meet different workload needs, giving you the freedom to pay only for what you use.

The costs are broken into key components like on-demand instances, database storage, I/O operations, backup storage, and data transfer, along with advanced features such as Elastic Clusters and Global Clusters. This detailed structure ensures clear, predictable costs while helping you optimize spending for your unique requirements.

Note: All pricing examples in this guide are based on the Ohio (us-east-2) AWS region. Pricing may vary by region, so it’s essential to verify costs for your selected region on the Amazon DocumentDB Pricing Page.

Pricing Components

1. On-Demand Instances:

• ‍Description: Charges are based on the compute capacity (vCPUs and memory) of the instances in your cluster.‍
• Billing: Per-second billing with a 10-minute minimum, providing cost efficiency for varying workloads.

2. Database Storage:

• ‍Description: Costs associated with the amount of data stored in your cluster’s storage volume.‍
• Billing: Priced per GB per month, with storage automatically scaling in 10 GB increments up to 128 TiB.

3. I/O Operations:

• ‍Description: Charges for read and write operations to your database storage.‍
• Billing: Priced per million I/Os, applicable under the Standard configuration.

4. Backup Storage:

• ‍Description: Storage used for automated backups and any manual snapshots beyond your cluster’s data storage size.‍
• Billing: Equivalent to 100% of your cluster’s data storage is provided at no additional cost each month; excess backup storage is billed per GB per month.

Amazon DocumentDB Free Trial

You can start exploring Amazon DocumentDB for free with the AWS Free Tier. First-time users are eligible for a one-month free trial that includes:

• 750 instance hours of db.t3.medium usage.
• 30 million I/Os for database operations.
• 5 GB of database storage.
• 5 GB of backup storage.

After the trial ends or if you exceed these limits, you can either shut down your cluster to avoid charges or continue at standard on-demand rates.

Amazon DocumentDB Elastic Clusters Pricing

Amazon DocumentDB Elastic Clusters let you seamlessly scale your database to handle millions of reads and writes with petabytes of storage. With no upfront costs, you only pay for the resources you use.

Elastic Clusters Pricing

• vCPU Usage: $0.132 per vCPU-hour (billed per minute, 10-minute minimum).
• Database Storage: $0.30 per GB-month for data, indexes, and change stream storage.
• Backup Storage: Free for up to 100% of your cluster’s database storage in the region. Excess storage costs $0.021 per GB-month.

Example Costs

• vCPU Usage: 16 vCPUs running for 100 hours = $211.20
• Storage: 500 GB for 1 month = $150
• Backup Storage: 100 GB excess backup = $2.10

Amazon DocumentDB Global Clusters Pricing

Amazon DocumentDB Global Clusters enable fast replication across AWS regions with latencies of less than one second. This ensures low-latency reads and improved disaster recovery without impacting workload performance.

Pricing

• Replicated Write I/Os: $0.20 per million replicated write I/Os between the primary and each secondary region.
• Additional Costs: Standard DocumentDB rates apply for instances, storage, cross-region data transfer, and backup storage.

Data Transfer Pricing

Amazon DocumentDB includes charges for data transfer in and out of clusters.

• Data Transfer IN: Free of charge.
• Data Transfer OUT:
  • Up to 9.999 TB/month: $0.09 per GB
  • Next 40 TB/month: $0.085 per GB
  • Next 100 TB/month: $0.07 per GB
  • Over 150 TB/month: $0.05 per GB

Backup Storage

Amazon DocumentDB backup storage includes automated backups and manual snapshots, allocated by AWS region.

Key Details

• Backup storage up to 100% of your cluster’s storage in a region is free.
• Retaining manual snapshots or increasing the backup retention period consumes additional storage.

Pricing

• $0.021 per GB-month for backup storage beyond the free tier.

Note: Copying snapshots to another region incurs additional charges in the destination region. Backup storage is free if retention is set to one day and no manual snapshots are retained.

Azure Cosmos DB Pricing

Azure Cosmos DB is a globally distributed, multi-model database service offered by Microsoft Azure. It provides seamless scalability and low-latency access to data, making it an ideal choice for applications requiring high availability and performance across multiple regions. Azure Cosmos DB supports a variety of APIs, including NoSQL, MongoDB, PostgreSQL, Cassandra, Gremlin, and Table, offering flexibility for diverse use cases.

Azure Cosmos DB’s pricing model is designed to be flexible, allowing users to pay only for what they use. Costs are categorized into three main components: compute, storage, and bandwidth. Once you choose a compute pricing model and API, it cannot be changed, so selecting the right combination is crucial.

Note: The prices in this guide are for the East US region. Pricing may vary by region, so check the Azure Cosmos DB Pricing Page for details in your area.

Compute Pricing

Azure Cosmos DB offers flexible compute pricing, tailored to the API and workload requirements. Costs are primarily measured through Request Units (RU/s) or vCores, depending on the API selected.

Request Unit (RU) Pricing

RUs measure the compute, memory, and I/O resources required to process database operations. This option applies to the NoSQL, MongoDB (RU), Cassandra, Gremlin, and Table APIs. RUs are billed per second and vary based on the API and deployment region.

RU-Based Options:

1. Standard Provisioned Throughput:
   • Pre-defined RU/s levels that deliver consistent performance.
   • Ideal for applications with predictable, stable workloads.
2. Autoscale Provisioned Throughput:
   • Dynamically scales RU/s up or down based on traffic demands.
   • Prevents over-provisioning during low-traffic periods, making it a great fit for variable workloads.
3. Serverless:
   • Pay-as-you-go model, where you’re charged only for the RUs consumed.
   • Designed for intermittent or unpredictable workloads, as well as lightweight or development applications.

vCore Pricing

For the PostgreSQL and MongoDB (vCore) APIs, Azure Cosmos DB uses a vCore-based pricing model:

• Billing: Charges are based on the number and size of vCore nodes provisioned.
• Use Case: Ideal for applications requiring traditional SQL compatibility or high-performance needs.

Storage Pricing

Storage costs in Azure Cosmos DB are based on the amount of data and indexes used and vary depending on the API.

Consumed Storage

For NoSQL, MongoDB (RU), Cassandra, Gremlin, and Table APIs:

• Billing: Charged per GB of data stored, covering transactional and analytical data, indexes, and backups.
• Rounding: Storage is rounded up to the nearest GB for each container, collection, table, or graph in each region.

Bandwidth Pricing

Bandwidth costs, also known as data egress, are incurred when data is transferred outside of Azure or between Azure regions and availability zones.

Data Egress

• Billing: Azure charges for data leaving the Azure cloud or crossing regions or availability zones via the Azure WAN.
• Applicable APIs: Bandwidth charges apply to all APIs, including NoSQL, MongoDB, Cassandra, Gremlin, and Table.

Tip: Careful planning of cross-region replication and data transfer can help reduce unnecessary bandwidth costs while maintaining performance and availability.

Azure Cosmos DB Throughput Types

Azure Cosmos DB offers three throughput options, each tailored to different workload patterns and traffic demands. Choosing the right model helps balance performance and cost.

1. Manual Provisioned Throughput
   • Description: Pre-set a fixed amount of Request Units (RUs) per second, such as 500 RU/s, billed hourly based on the maximum provisioned RUs. For example, if you set 8,000 RU/s but later reduce it to 4,000 RU/s, you’ll still be billed at 8,000 RU/s for that hour.
   • Minimum: Requires a minimum of 400 RU/s.
   • Use Case: Best suited for steady, consistent traffic, such as a web application with predictable usage.
   • Adjustments: Throughput can be modified in increments, making it easy to plan predictable monthly costs.
2. Autoscale Provisioned Throughput
   • Description: Dynamically adjusts RU/s based on workload demands, scaling between 10% and 100% of a defined maximum (e.g., 1,000 to 4,000 RU/s). Billing is based on the highest RU/s used each hour. As data grows, the baseline RU/s may increase.
   • Minimum: Starts at 1,000 RU/s, with throughput scaling between 100 and 1,000 RU/s as needed.
   • Use Case: Ideal for applications with fluctuating demand, such as a social app with peak activity in the evenings.
   • Flexibility: Automatically accommodates traffic spikes without manual adjustments.‍
3. Serverless Throughput
   • ‍Description: Pay-as-you-go model where you’re billed only for the RUs consumed by actual requests, up to a maximum of 5,000 RU/s. This option automatically scales with workload needs.‍
   • Use Case: Perfect for development, testing, or applications with intermittent traffic.‍
   • Limitations: Designed for single-region use with lighter workloads. There is a data size cap per container and an RU/s limit.

These throughput models cater to various workload types, allowing you to align performance with budget while optimizing Cosmos DB for specific use cases.

Budget-Friendly Solutions

If you’re working with a tight budget or simply want to explore MongoDB without committing to a managed service, consider these options:

• MongoDB Community Edition (Self-Hosted): The fully featured open-source version of MongoDB. While hosting and managing everything yourself is more hands-on, it offers total control over configuration.
• Free Tiers (Atlas, AWS, Azure, GCP): Many providers offer free or low-cost tiers to help you get started. These tiers typically have limitations on storage, CPU, and memory, but they’re perfect for small projects or development environments.

How to Choose the Right Provider

With multiple providers and pricing models, the decision-making process can feel overwhelming. To narrow down your choices, consider the following:

1. Scalability Needs
   • If you anticipate significant growth or variable workloads, a serverless or auto-scaling plan can help avoid provisioning too much or too little.
   • Evaluate how each provider handles sharding, replication, and global distribution.
2. Workload Characteristics
   • High-throughput read/write apps may be more cost-efficient on a plan that bundles compute and I/O in a single rate (e.g., Request Units).
   • Steady, predictable workloads might benefit from discounted reserved instances or provisioned capacity.
3. Budget Constraints
   • Compare monthly costs across providers based on the cluster tier or instance size you need.
   • Pay attention to hidden costs like data transfer, backups, or cross-region replication.
4. Technical Ecosystem and Support
   • If you’re already invested in AWS, Azure, or GCP, it might make sense to leverage the native solutions for seamless integration.
   • For specialized MongoDB support and advanced features, MongoDB Atlas may offer a more direct path to expert guidance.
5. Operational Overhead
   • Self-hosting provides the most control but places the onus of management, patching, and troubleshooting on you.
   • Managed services reduce operational burden and typically include robust monitoring and support.

Actionable Insight: Make a checklist of your key requirements—data size, expected throughput, compliance needs, and growth projections. Then compare the pricing calculators and tiers of each provider against your checklist. This practical approach helps you avoid overspending and ensures you have enough headroom to accommodate future demands.

Conclusion

Selecting the right MongoDB solution is about more than just technical compatibility—it’s about aligning performance, scalability, and budget with your unique requirements. This blog has outlined the core pricing models of MongoDB and its major providers, such as Atlas, AWS, and Azure, offering you insights into their strengths, billing structures, and cost considerations.

For those starting small or exploring MongoDB, free options like the shared tiers or self-hosted Community Edition provide a budget-friendly entry point. Meanwhile, production-grade applications benefit from dedicated clusters, serverless options for unpredictable workloads, or enterprise-grade solutions for compliance and high availability.

Finally, remember to carefully evaluate workload patterns, scalability needs, and total cost of ownership. Whether you’re optimizing for steady traffic or seasonal spikes, balancing these factors will help you make a confident, informed decision.

The choice of a provider isn’t just about saving money—it’s about creating a reliable, future-ready database foundation. Use the insights shared here to pick a solution that fits your needs today and scales effortlessly with your growth tomorrow. For more details, explore each provider’s pricing calculator to model costs tailored to your use case.