Document Database in Practice - Flexible Data Modeling with Amazon DocumentDB and DynamoDB
Learn how to design and operate document databases using Amazon DocumentDB and DynamoDB.
Document Database Fundamentals and AWS Service Options
A document database is a NoSQL database designed to store and query flexible data structures in JSON or BSON format. Unlike relational databases, you do not need to strictly define a schema in advance, allowing you to flexibly change data structures as your application evolves. AWS offers two services for document database use cases: Amazon DocumentDB and Amazon DynamoDB. DocumentDB provides a MongoDB-compatible API, enabling you to migrate existing MongoDB applications with minimal changes. DynamoDB, on the other hand, is a fully managed service that supports both key-value and document models, delivering consistent single-digit millisecond latency. Running a MongoDB cluster on-premises involves significant operational overhead, including replica set configuration, sharding design, backup automation, and security patching, all of which are automated by AWS managed services.
Features of Amazon DocumentDB
Amazon DocumentDB is a managed database service compatible with MongoDB 3.6, 4.0, and 5.0. Storage automatically scales up to 128 TiB and maintains six copies across three Availability Zones for high durability and availability. You can add up to 15 read replicas to easily distribute read workloads. DocumentDB's storage engine is SSD-based and uses quorum-based replication, where a write is considered complete once confirmed by four of the six copies. The global clusters feature enables replication across up to five regions, providing both disaster recovery and global read performance. Below is an example CLI command to create a DocumentDB cluster. aws docdb create-db-cluster \ --db-cluster-identifier my-docdb-cluster \ --engine docdb \ --engine-version 5.0.0 \ --master-username admin \ --master-user-password MySecurePassword123 \ --storage-encrypted
DynamoDB's Document Model and Use Cases
DynamoDB also excels at storing document-type data. Each item can hold nested JSON structures up to 400 KB, freely combining map and list attributes to represent documents. Using PartiQL, a SQL-compatible query language, you can intuitively write searches and updates targeting specific fields within nested documents. DynamoDB's on-demand capacity mode automatically scales with traffic, and costs are near zero during periods with no requests. It is ideal for use cases with well-defined access patterns and scalability requirements, such as game player profiles, e-commerce product catalogs, and IoT device telemetry data. By combining DynamoDB Streams with Lambda, you can build event-driven architectures that detect document changes in real time and propagate them to downstream systems. The global tables feature also enables active-active configurations across multiple regions. For a comprehensive guide to data modeling with MongoDB, technical books (Amazon) are a great reference.
Choosing Between DocumentDB and DynamoDB
Both DocumentDB and DynamoDB can handle document data, but they are optimized for different use cases. DocumentDB is best when complex query patterns are needed. You can leverage MongoDB's rich query capabilities, including ad-hoc queries, aggregation pipelines, text search, and geospatial queries. It is also the ideal migration target for existing MongoDB applications. DynamoDB, on the other hand, is suited for workloads where access patterns can be defined in advance and consistent single-digit millisecond latency is required. It excels in use cases where high throughput and low latency are critical, such as session management, shopping carts, and real-time bidding systems. When migrating from on-premises MongoDB, the general guideline is to choose DocumentDB based on query complexity, and DynamoDB when scalability is the top priority for new development. Both services support encryption, VPC integration, and IAM authentication, meeting enterprise-level security requirements.
Pricing Comparison Between DocumentDB and DynamoDB
A DocumentDB db.r6g.large instance costs approximately $199/month, with storage at about $0.10 per GB/month. DynamoDB on-demand mode charges approximately $0.25 per million read units and $1.25 per million write units. DynamoDB is serverless with near-zero minimum cost, while DocumentDB incurs fixed instance costs. Choose DynamoDB for simple access patterns with high throughput, and DocumentDB when complex queries and aggregations are needed.
Summary - Optimizing Your Document Database Strategy
DynamoDB provides serverless scalability and consistent low latency, with native Lambda integration that makes building event-driven architectures easy. By choosing the right service for your workload characteristics, you can achieve both flexible data modeling and high performance. The key to selecting a document database is to evaluate three factors: query pattern complexity, scalability requirements, and leveraging existing assets.