MongoDB
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What is MongoDB?
MongoDB is a modern document database designed to help developers build applications faster by storing data in flexible, JSON-like documents. It maps naturally to objects in application code, eliminating the need for complex object-relational mapping. The flexible schema allows data models to evolve without downtime, making it ideal for handling non-uniform data and rapid iteration.
MongoDB Atlas is the fully managed AI-ready data platform that combines operational data, vectors, and streaming data in a unified platform. Key features include Vector Search for semantic search and generative AI applications, Stream Processing for event-driven applications, built-in full-text search, geospatial queries, graph data support, time series collections, and multi-document ACID transactions. It supports horizontal scaling through sharding, built-in high availability with automatic failover, and works seamlessly across AWS, Azure, and Google Cloud.
MongoDB is for developers and enterprises building modern applications ranging from rapid prototyping to large, mission-critical workloads. It serves retail, automotive, telecommunications, healthcare, and financial services industries. The platform is loved by builders for its developer-friendly API and trusted by enterprises for its reliability, scalability, and 99.99% availability.
MongoDB pricing
Pricing model: Freemium
MongoDB Atlas offers a free forever M0 tier with 512 MB storage, 32MB sort memory, and up to 100 operations per second. Shared developer tiers include M2 (2 GB storage) at $9/mo and M5 (5 GB storage) at $25/mo. Dedicated production tiers range from M10 ($0.08/hr with 2 GB RAM, 2 vCPUs, 10-128 GB storage) to M700 ($33.26/hr with 768 GB RAM, 96 vCPUs, 4 TB storage). Additional pricing includes Atlas SQL Interface at $5 per TB data processed, Atlas Data Lake starting at $0.048 per GB per month, Atlas Search from $0.12/hr, Stream Processing from $0.06/hr, and Atlas App Services with 1 million requests/month free tier. Discounts available for startups, educators, and students through free credits programs.
MongoDB pros
- Stores data in flexible JSON-like documents
- Document model maps to application code objects
- Flexible schema evolves without downtime
- Built-in horizontal scaling through sharding
- High availability with automatic failover
- Multi-document ACID transactions supported
- Vector Search built into the same platform
- Stream Processing with MongoDB Aggregation Pipeline
- Native geospatial support with GeoJSON
- Full-text search eliminates separate search engine
- Graph data support for relationship analysis
- Time series collections for temporal data
- 100+ technology integrations available
- Free forever M0 tier with 512 MB storage
- Scales from prototype to mission-critical workloads
- No complex object-relational mapping needed
- Ad hoc queries with powerful query engine
- Real-time aggregation capabilities
- Geographic distribution built into core architecture
- 30%-50% faster with combined database and search
MongoDB cons
- Free tier limited to 512 MB storage
- Shared RAM and vCPU on entry tiers
- Higher cost for dedicated production clusters
- Memory usage higher than relational databases
- No native joins in older versions
- Transaction overhead compared to single documents
- Free tier limited to 100 operations per second
- Charts auto-refresh limited to every 4 hours on M0
- Data transfer costs based on cloud provider rates
- Complex schema validation requires JSON Schema knowledge
Frequently asked questions about MongoDB
What is MongoDB?
MongoDB is a document database designed to help developers build modern applications faster. It stores data in flexible, JSON-like documents, making it easy to model data the same way your application code uses it. The flexible schema lets you evolve your data model without downtime, iterate quickly, and easily handle non-uniform data. MongoDB provides a powerful query engine, horizontal scaling, and built-in high availability.
Is MongoDB free to use?
Yes, MongoDB is free to use. MongoDB Atlas offers a free-forever M0 tier with 512 MB of storage, 32MB of sort memory, and up to 100 operations per second. The free tier is a great starting point to learn about MongoDB and explore its capabilities in a fully managed cloud environment. MongoDB Community Server is also available for free download for self-managed deployments.
What is MongoDB Atlas?
MongoDB Atlas is the modern, AI-ready data platform that combines operational data, vectors, and streaming data in a unified platform. It is a fully managed service available on AWS, Azure, and Google Cloud. Atlas includes Vector Search, Stream Processing, built-in search, geospatial queries, graph support, time series collections, and automatic scaling. It is trusted by enterprises for 99.99% availability.
How does MongoDB scale?
MongoDB natively supports horizontal scaling through sharding, which automatically partitions data based on a shard key and distributes it across a cluster of machines. Sharding enables automatic data distribution, zone sharding for geographical placement, and shard key refinement as applications evolve. This allows MongoDB to handle large datasets and high throughput without downtime.
Does MongoDB support transactions?
Yes, MongoDB supports multi-document ACID transactions. These let you run multiple read and write operations as a single all-or-nothing event with atomicity, consistency, isolation, and durability guarantees. Transactions span multiple documents while maintaining data consistency and can coordinate across sharded clusters with the same ACID guarantees.
What is MongoDB Vector Search?
MongoDB Atlas integrates operational and vector databases in a single, unified platform. Vector Search uses vector representations of your data to perform semantic search, build recommendation engines, design Q&A systems, detect anomalies, or provide context for generative AI applications. It eliminates the need for separate vector database solutions.
What cloud providers does Atlas support?
MongoDB Atlas is available on AWS, Azure, and Google Cloud. You can deploy clusters on any of these three major cloud providers. Resource policies can restrict cloud provider selection to ensure clusters are only deployed on approved providers, supporting regulatory or business requirements for data residency.
How does MongoDB handle high availability?
MongoDB's built-in replication mechanism provides automatic failover, data redundancy, and increased read capacity. With automatic failover, if the primary server becomes unavailable, the cluster automatically elects a new primary to ensure writes remain available. Multiple copies of data are stored across different servers to improve data durability, achieving 99.99% availability for customers.
What is the difference between MongoDB and MySQL?
MongoDB is a non-relational document database offering improved flexibility and horizontal scalability, while MySQL is a relational database with rigid structure. MongoDB documents map naturally to modern object-oriented programming languages, removing the complex object-relational mapping layer. MongoDB scales easily within and across distributed data centers without downtime, whereas achieving scale with MySQL often requires significant custom engineering work. MongoDB is often faster for retrieving single documents compared to JOINs across multiple tables in MySQL.
What use cases is MongoDB best for?
MongoDB supports a wide range of workload types including document-based structured search (OLTP), data aggregation, full-text search, vector search, geospatial search, and time series data. It is ideal for catalog and content search, recommendation engines, fraud detection, logistics and location-based services, event-driven applications, analytics in real-time, and AI-native applications requiring both operational and vector data in one platform.