Amazon DocumentDB features

Amazon DocumentDB Serverless automatically scales database capacity up or down to meet your application workload needs, and supports all Amazon DocumentDB features including Multi-AZ deployments and read replicas. For variable workloads, it offers up to 90% cost savings as compared to provisioning for peak capacity. You can choose to configure all the instances in your database cluster to use the DocumentDB Standard or I/O-Optimized storage configuration based on the price performance and price predictability needs of your application. You pay on a per-second basis for the database capacity you use when the database is active. 

Amazon DocumentDB will automatically grow the size of the storage volume as your cluster storage needs grow. The storage volume will grow in increments of 10 GiB up to a maximum of 4 PiB. You don't need to provision excess storage for your document database to handle future growth.

With a few clicks in the AWS Management Console, you can scale the compute and memory resources up or down by creating new replica instances of the desired size or by removing instances. Compute scaling operations typically complete in a few minutes.

You can scale-out read throughput to support high volume application requests by creating up to 15 database read replicas. Amazon DocumentDB replicas share the same underlying storage as the source instance, lowering costs and avoiding the need to perform writes at the replica nodes. This frees up more processing power to serve read requests and reduces the replica lag time–often down to single digit milliseconds. Amazon DocumentDB also provides a single endpoint for read queries so the application can connect without the need to keep track of replicas as they are added and removed.

Amazon DocumentDB has a flexible JSON document model, data types, and efficient indexing. It uses a scale-up, in-memory optimized architecture to allow for fast query evaluation over large documents sets.

Amazon DocumentDB Elastic Clusters enables you to handle millions of writes and reads per second, allowing you to scale their document databases in minutes with little to no downtime or impact to performance. You can also store petabytes of data and only pay for the capacity you consume with zero management of underlying infrastructure.

The health of your Amazon DocumentDB cluster and its instances are continuously monitored. If the instance powering your database fails, the instance and associated processes are automatically restarted. Amazon DocumentDB recovery does not require the potentially lengthy replay of database redo logs so your instance restart times are typically 30 seconds or less. It also isolates the database cache from database processes, allowing the cache to survive a database restart.

If there is instance failure, Amazon DocumentDB automates failover to one of up to 15 Amazon DocumentDB replicas you created in any of three Availability Zones. If no Amazon DocumentDB replicas have been provisioned, in the case of a failure, Amazon DocumentDB will attempt to create a new instance for you automatically.

Amazon DocumentDB Global Clusters improves your disaster recovery posture in the rare event of a Region-wide outage and enables low-latency global reads. It uses fast storage-based physical replication of data across Regions with typical lag of less than one second. The replication utilizes dedicated infrastructure so there's no impact to your workload’s performance.

In the unlikely event of a regional degradation or outage, one of the secondary regions can be promoted to full read/write capabilities in less than one minute. You can have up to 10 secondary regions with Global Clusters, and each secondary region can have up-to 16 replica instances. Each secondary cluster can be scaled independently as the number and type of instances in the primary and secondary clusters don’t need to be the same. Scaling instances in Amazon DocumentDB takes less than 10 minutes, regardless of the data volume. 

Global Clusters enable global reads with low latency so users can read data from secondary clusters in Regions that are closest to them. It serve reads locally with low latency from secondary clusters, while using the primary cluster for writes, helping optimize for use cases with a high read to write ratio. You can create a new Global Cluster or add regions to existing clusters with just a few clicks on the  AWS Management Console , or by using the AWS SDK or CLI.

Amazon DocumentDB makes your data durable across three Availability Zones (AZs) amd you only pay for one copy. It uses fault-tolerant storage that transparently handles the loss of up to two copies of data without affecting database write availability and up to three copies without affecting read availability. Its storage is also self-healing; data blocks and disks are continuously scanned for errors and replaced automatically.

Amazon DocumentDB offers a simple database backup capability that enables point-in-time recovery for clusters. You can restore your cluster to any second during the retention period, up until the last five minutes. The automatic backup retention period can be configured up to thirty-five days. Automated backups are stored in Amazon S3, which is designed for 99.999999999% (11 9s) durability. Backups are automatic, incremental, and continuous and have no impact on cluster performance.

Cluster snapshots are user-initiated backups of cluster stored in Amazon S3 that will be kept until explicitly deleted. They leverage the automated incremental snapshots to reduce the time and storage required. You can create a new cluster from a cluster snapshot whenever desired.

Amazon DocumentDB runs in Amazon Virtual Private Cloud (Amazon VPC), which allows you to isolate the cluster in the virtual network and connect to on-premises IT infrastructure using industry-standard encrypted IPsec virtual private networks (VPNs). In addition, using its VPC configuration, you can configure firewall settings and control network access to the cluster.

Amazon DocumentDB supports role-based access control (RBAC) with built-in roles and defined roles. With RBAC, you can enforce least privilege as a best practice by restricting the actions that users are authorized to perform. Amazon DocumentDB is also integrated with AWS Identity and Access Management (IAM) which lets you control the actions that AWS IAM users and groups can take on specific Amazon DocumentDB resources, including clusters, instances, snapshots, and parameter groups. In addition, you can tag the Amazon DocumentDB resources and control the actions that the IAM users and groups can take on groups of resources that have the same tag (and tag value).

Amazon DocumentDB allows you to encrypt databases using keys created and controlled through AWS Key Management Service (KMS). On a cluster running with Amazon DocumentDB encryption, data stored at rest in the underlying storage is encrypted as are the automated backups, snapshots, and replicas in the same cluster. By default, connections between a client and Amazon DocumentDB are encrypted-in-transit with TLS.

Amazon DocumentDB makes it easy for you to meet your regulatory and compliance obligations. Amazon DocumentDB complies with PCI DSS, ISO 9001, ISO 27001, ISO 27017, ISO 27018, SOC 1, 2 and 3, and Health Information Trust Alliance Common Security Framework certification (HITRUST CSF), in addition to being HIPAA eligible.

Amazon DocumentDB has transparent pricing with no hidden costs and no upfront commitment. You pay an hourly charge for each instance that you launch and when you’re finished, you can delete or pause the instance. DocumentDB decouples compute and storage, enabling the independent scaling of each according to workload needs, thereby reducing your costs. To see more details, visit the Amazon DocumentDB pricing.

Amazon DocumentDB offers I/O-Optimized storage configuration for those seeking price predictability. I/O-Optimized offers up to 40% cost savings for I/O-intensive applications where I/O charges exceed 25% of the total Amazon DocumentDB database spend. With Amazon DocumentDB I/O-Optimized, you can effectively eliminate the uncertainty of variable I/O charges. Instead, you are billed only for compute, storage, and backup charges, ensuring price predictability and transparency.

Amazon DocumentDB enables you to choose between Standard and I/O-Optimized storage configurations for your database cluster. The flexibility enables you to maximize price performance by choosing the appropriate configuration based on your needs. If your application requires low to moderate I/O consumption, Standard is the right storage configuration. However, if your application is I/O-intensive, you should consider I/O-Optimized, which provides improved price performance with up to 40% cost savings.

Amazon DocumentDB is compatible with MongoDB 3.6, 4.0, and 5.0 drivers and tools. A vast majority of the applications, drivers, and tools that customers already use today with their open source MongoDB database can be used with Amazon DocumentDB with zero changes. Amazon DocumentDB emulates the responses that a client expects from a MongoDB server by implementing the Apache 2.0 open source MongoDB 3.6, 4.0, and 5.0 APIs on a distributed, fault-tolerant, and self-healing storage system that gives customers the performance, scalability, and availability they need when operating mission-critical MongoDB workloads at scale. Learn more about supported MongoDB APIs.

Geospatial query capabilities enables you to use Amazon DocumentDB to support storing, querying and indexing geospatial data. You can create 2dsphere indexes and use popular MongoDB geospatial APIs such as $nearSphere, $geoNear, $minDistance, $maxDistance to perform queries stored on data stored in Amazon DocumentDB.

ACID (atomicity, consistency, isolation, durability) is a set of properties of database transactions intended to guarantee data validity despite errors, power failures, and other mishaps. Starting with MongoDB 4.0 API, Amazon DocumentDB supports the ability to perform ACID transactions across multiple documents, statements, collections, and databases.

You can easily migrate your on-premises or self-managed (on Amazon EC2) MongoDB databases to Amazon DocumentDB with virtually no downtime using the AWS Database Migration Service (DMS). With DMS, you can migrate from a MongoDB replica set or from a sharded cluster to Amazon DocumentDB. For more information about migrating both relational and non-relational databases to Amazon DocumentDB, see Migrating to Amazon DocumentDB.

To get started with Amazon DocumentDB, you simply launch a new Amazon DocumentDB cluster using the AWS Management Console. Amazon DocumentDB instances are pre-configured with parameters and settings appropriate for the instance class selected. You can create a cluster and connect the application within minutes without any additional configuration.

Amazon DocumentDB is integrated with Amazon CloudWatch, which provides metrics for your database instances. You can use the AWS Management Console to view over 40 key operational metrics for the cluster, including compute, memory, storage, query throughput, MongoDB opcounters, and active connections.

Amazon DocumentDB will keep customers’ databases up-to-date with the latest patches. You can control if and when the cluster is patched with Database Engine Version Management.

Amazon DocumentDB has native integrations with many other AWS services to extend functionality, including Amazon CloudWatch for monitoring and alarms, AWS CloudTrail for audit logs, AWS Identity and Access Management (IAM) for resource permissions, AWS Lambda for event-driven architectures, AWS Key Management Service (KMS) for encryption keys, AWS Secrets Manager for secure password management, AWS Glue for ETL, Amazon OpenSearch Service for search analytics, and Amazon SageMaker Canvas for machine learning.

Amazon DocumentDB offers native vector database capabilities including vector storage, indexing, search, and retrieval. You can search millions of vectors with millisecond latency. You can store vectors from Amazon Bedrock, Amazon SageMaker, and other third party models. Additional information is provided in the vector search for Amazon DocumentDB documentation.  

Amazon DocumentDB integrates with Amazon SageMaker Canvas, making it easy to build generative applications using data stored in Amazon DocumentDB. The in-console integration removes the undifferentiated heavy lifting to connect and access Amazon DocumentDB to accelerate your AI/ML development with a low code/no code experience. You can build AI/ML models for classic use cases such as regression and forecasting, or create generative AI solutions such as content generation, text extraction, and text summarization within SageMaker Canvas. Additional information is provided in the Amazon DocumentDB generative AI documentation.

Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service provides advanced search capabilities (such as fuzzy search, semantic search, and more) for data stored in Amazon DocumentDB using the OpenSearch API. With this integration, you can also uniquely search across collections and other non-English languages. With a few clicks in the AWS Console, you can now seamlessly synchronize your data from Amazon DocumentDB to OpenSearch Service, eliminating the need to write any custom code to extract, transform, and load the data.

This zero-ETL integration uses Amazon OpenSearch Ingestion which seamlessly moves document data from Amazon DocumentDB to Amazon OpenSearch Service. It automatically understands the format of the data in Amazon DocumentDB collections and maps the data to OpenSearch Service to yield the most performant search results. This zero-ETL integration enables consolidation from multiple Amazon DocumentDB collections into one OpenSearch Service managed cluster or serverless collection. Additional information is provided in Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service documentation.