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Amazon DocumentDB: Understanding what it is and when to use it

The ultimate guide to Amazon DocumentDB databases
This article delves deep into the intricacies of Amazon DocumentDB, its comparison with other databases, and its potential benefits.
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Businesses are constantly looking for efficient and scalable solutions to manage their data. Amazon DocumentDB is a fully managed document database service. It offers the performance, scalability, availability, security, and compatibility of MongoDB with the ease of use and management of a managed service.

This article delves deep into the intricacies of Amazon DocumentDB, its comparison with other databases, and its potential benefits. 

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What is a Document Database?

A document database is a flexible and NoSQL type database. It stores data in JSON-like documents and can be of varying sizes and structures, making it a good fit for storing complex data.

Document databases are useful for apps that require querying and storing large amounts of data. This data can be semi-structured or unstructured, such as gaming applications, social media applications, and web applications. These types of databases are also referred to as non-relational (or NoSQL) databases.

Non-Relational (NoSQL) Databases

Non-relational databases offer some key differences from traditional relational databases. Relational databases normally store data in tables with fixed rows and columns. Rows represent a complete record and columns represent an attribute of the record. Alternatively, non-relational databases can store data in graphs, key-value pairs, and documents.

Benefits of Document Databases

There are several benefits of document databases, including:

  • Flexibility: They can store data of varying sizes and structures, so they are good for storing complex data.
  • Scalability: They are easily scalable to application requirements.
  • Performance: These databases offer very high performance, especially for processing a large volume of queries.
  • Ease of use: They are often easier to use than relational databases, especially for developers who are not familiar with SQL.

Given the benefits of document databases, they are continuing to increase in popularity and usage.

Examples of Document Databases

Popular document databases include:

  • Amazon DocumentDB: a fully managed document database service that is based on MongoDB. It offers high availability, scalability, and security.
  • MongoDB: an open-source document database that is widely used by developers. It is known for its high levels of flexibility and scalability.
  • CouchDB: an open-source document database that is distributable and fault-tolerant.
  • DynamoDB: a fully managed NoSQL database service that is designed for high performance and low latency. It can process a large number of requests per second.

As these databases are all NoSQL, they have some stark differences from SQL databases.

Comparison to SQL Databases

The main difference between document databases and SQL databases is the way in which they store data. Document databases store data in documents, while SQL databases store data in tables. This results in some notable variations between the two.

Below is a table comparing document databases and SQL databases:

FeatureDocument databaseSQL database
Data storageDocumentsTables
Data structureFlexibleRigid
QueriesJSON-like queriesSQL queries
PerformanceVery performant for handling complex queriesLess performant for handling complex queries
Ease of useEasier to use for developers who are not familiar with SQLHarder to use for developers who are not familiar with SQL

Data Stored in JSON-like Documents

Storing documents in a document database is similar to using JavaScript Object Notation (JSON) objects. JSON is a lightweight data-interchange format that is easy to read and write. This similarity makes document databases a good choice for applications that need to store data that is easily readable for humans. Here are some benefits of using document databases in the context of their JSON-like characteristics:

Map Naturally to How Humans Model Data

Documents are a natural way to model data that is complex or unstructured, such as user profiles (e.g., names, email addresses, phone numbers).

Example data showing product info

Flexible Schema and Indexing

Document databases have a flexible schema. They can change data structures without recreating the database, making them a good solution for evolving applications. Without a fixed schema you have the flexibility to define relationships through code so that you’re not bound by the limits of table definitions.  

Example data for a customer purchase

Indexing and the way that you store data provide speed and performance optimization for queries. Certain data types are ideal for this formatting and structure.  

Expressive Query Language

Document databases typically have an expressive query language that allows the user to query data in a variety of ways. This makes it easy to find complex or even unstructured data.

Query and retrieval for unstructured data example

Unstructured data query and retrieval is different from SQL databases because it allows for very flexible, expressive queries that aren’t bound by a fixed schema and set of relationships. 

What is Amazon DocumentDB?

Broad Definition

Amazon DocumentDB is a fully managed NoSQL database service designed for JSON data management at scale. It offers compatibility with MongoDB, ensuring seamless transition between several applications. Amazon DocumentDB is defined by its core attributes:

  • Fully managed NoSQL database service: Amazon Web Services (AWS) manages the operational aspects of running the database, such as cloud backups, patching, and scaling. This allows businesses to focus on application development.
  • Built for JSON data management at scale: It is designed to handle vast amounts of JSON-formatted data while ensuring high performance as data volumes surge.
  • Compatibility with MongoDB: Amazon DocumentDB’s compatibility with MongoDB Application Programming Interfaces (APIs) ensures that businesses using MongoDB can easily transition to Amazon DocumentDB without significant codebase alterations.

Supported Applications

  • Big data applications: Amazon DocumentDB can store and query large amounts of data, such as customer transactions, social media data, and sensor data.
  • Gaming applications: Store and query the game state, player data, and game object with Amazon DocumentDB.
  • Real-time web/mobile apps: You can use DocumentDB to store and query real-time data, such as user sessions, shopping cart activity, and game scores.
  • Online shopping/advertising: Amazon DocumentDB can store and query product information, customer orders, and advertising data.
  • Social media apps: Take advantage of Amazon DocumentDB to store and query user profiles, posts, and comments.
  • Content management: Use Amazon DocumentDB to store and query website content, such as news articles, blogs, and product catalogs.

While the use cases of Amazon DocumentDB vary, it still has some key definable qualities.

List of Characteristics

Characteristics of Amazon DocumentDB include:

  • High levels of scalability, availability, and performance for data intensive workloads.
  • A flexible schema that permits changes to the data structure without altering the database.
  • Automatic indexing that allows you to easily search and query data.
  • Replication of data across multiple availability zones (AZs) to protect against failure.
  • A pay-as-you-go pricing model, such that only services in use require payment.

However, there are some notable differences between Amazon DocumentDB and other document databases.

Amazon DocumentDB vs DynamoDB

While both DocumentDB and DynamoDB databases are part of the suite of AWS database services, they cater to different needs. DynamoDB, a key-value and document database, is designed for ultra-high performance at any scale. It offers a higher level of versatility, supporting both document and key-value data structures.

Conversely, DocumentDB is a pure document database, specifically tailored for JSON-like document data. It is optimal for programs that involve complex querying and data modeling capabilities.

Amazon DocumentDB vs MongoDB

Amazon DocumentDB offers compatibility with MongoDB, so it supports the same APIs that MongoDB does. However, the similarities largely end there.

DocumentDB is optimized for the AWS ecosystem, It provides features like integration with AWS Identity and Access Management (IAM) for security and Amazon CloudWatch for monitoring. Alternatively, MongoDB is a general-purpose document database that you can deploy within any cloud environment.

What is MongoDB Capability?

Amazon DocumentDB has compatibility with MongoDB, so they use the same APIs, drivers, and tools. This allows for easy migration from MongoDB to DocumentDB.

Some explicit proficiencies of Amazon DocumentDB that are compatible with MongoDB are:

  • Ability to use the existing MongoDB APIs for querying documents: Amazon DocumentDB and MongoDB utilize the same query language.
  • Ability to use existing MongoDB drivers and tools: Amazon DocumentDB supports the same drivers and tools as MongoDB.
  • ACID transactions across documents/databases: Amazon DocumentDB supports ACID transactions across documents and databases, as does MongoDB. This means that data is always consistent between the two, even if there are multiple concurrent operations.

In addition to these capabilities, Amazon DocumentDB offers many other features, such as:

  • Automatic scaling: DocumentDB automatically scales databases up or down according to requirements or workloads.
  • High availability: DocumentDB allows you to replicate data across multiple AZs. Therefore, data is always available, even if one AZ fails.
  • Security: DocumentDB offers many security features to protect data. These features include access control, encryption, and auditing.

There are even more benefits of Amazon DocumentDB outside of its ability to integrate with MongoDB.

What Are The Benefits Of Using Amazon DocumentDB?

Amazon DocumentDB has many positive attributes, including:

  • Speed: Amazon DocumentDB uses a variety of techniques to optimize performance for read/write operations, such as in-memory caching and parallel processing.
  • Scalability: It is highly scalable and can easily add or remove capacity. You can scale Amazon DocumentDB to handle millions of requests per second.
  • Flexibility: Amazon DocumentDB allows you to store and query data of any structure and does not require a rigid schema.
  • Availability and durability: It is highly available and durable, as it is able to replicate data across multiple AZs.
  • Resilience to failures: DocumentDB uses a variety of techniques to protect data from failures, such as automatic failover and data replication. However backing up your database with N2WS will ensure your data remains highly available.
  • Monitoring and metrics: It provides monitoring and metrics to track database performance. Amazon CloudWatch allows Amazon DocumentDB to collect and store metrics for easy viewing and analysis.
  • Security/compliance: DocumentDB is highly secure and compliant, offering several features to protect data. These include encryption, access control, and auditing. Amazon DocumentDB is also compliant with a variety of industry standards, such as HIPAA and PCI DSS.
  • Automated data management: You can use Amazon DocumentDB to automatically handle the undifferentiated work of data management, such as provisioning, cloud backups, and replication.
  • Decoupled storage and compute: Amazon DocumentDB decouples storage and compute, allowing cloud storage and compute to scale independently. This optimizes performance and costs.

These attributes contribute to a wide array of situations where you can employ Amazon DocumentDB.

When would you use Amazon DocumentDB?

Amazon DocumentDB can handle vast amounts of data with its high performance and flexibility. Some cases in which it can be useful include:

  • Big data applications: Amazon DocumentDB is able to manage large datasets, i.e. “big data,” that result from data-driven decision-making. This capability allows for rapid data retrieval and consistent performance. Moreover, Amazon DocumentDB’s distributed architecture ensures that as data grows, the database can scale horizontally. This means that it can accommodate increased loads without compromising speed.
  • Gaming applications: You can take advantage of DocumentDB’s ability to handle high-throughput operations and its low-latency data access for storing player profiles, game states, leaderboards, and more. This makes Amazon DocumentDB a good candidate for gaming backends, providing a seamless experience for players.
  • Real-time web/mobile apps: DocumentDB offers in-memory caching and optimized query processing to ensure that data is retrieved and displayed in real time. This is practical for web applications that require real time data access, such as chat applications and live tracking systems.
  • Online shopping/advertising: The flexible schema of DocumentDB allows for easy updates and modifications. This means that the most current data is always available for users and advertisers, which is useful for e-commerce platforms and advertising systems. These platforms often deal with dynamic data that changes frequently, such as product inventories and user preferences.
  • Social media applications: Amazon DocumentDB is a document-oriented structure, so it is well-suited for the dynamic and interactive nature of social media platforms. It facilitates smooth and responsive social interactions, which includes multi-structured data such as user posts, comments, likes, and shares.
  • Content management: The JSON-like cloud storage of DocumentDB is ideal for content management systems (CMS) requiring databases that can store diverse types of content. This contributes to easy categorization and retrieval of articles, blogs, and records.
  • Personalization: The expressive query language and indexing capabilities of Amazon DocumentDB make it a good choice for personalization engines. You can process and analyze user data efficiently for systems that offer product recommendations or that tailor content based on user behavior.  
  • Catalogs: Amazon DocumentDB offers a structured yet flexible way of storing catalog data that is practical for businesses with extensive product or service offerings. You can easily organize and access product categories, specifications, and other details, thanks to these hierarchical data structures.
  • IoT: The scalability and high availability of Amazon DocumentDB make it a preferred choice for Internet of Things (IoT) applications. IoT applications involve devices that generate massive amounts of data, such as industrial sensors, wearable tech smarts, or home devices. Amazon DocumentDB provides a robust backend database to store and process the data that these devices require, enabling continuous data flow and analysis.

In sum, Amazon DocumentDB provides a scalable, flexible, and highly performant database for storing and querying large amounts of data.

The tools and performance needed for efficient cloud storage

Amazon DocumentDB offers performance, scalability, availability, security, and compatibility of MongoDB with the ease of use and management of other managed services. DocumentDB is a great choice for a wide variety of applications, including big data, gaming, real-time web and mobile applications, online shopping/advertising, social media, content management, personalization, catalogs, and IoT.

The features and capabilities of Amazon DocumentDB make it stand out as a top choice for businesses looking for long-lasting cloud management solutions. Whether transitioning from MongoDB or starting anew, Amazon DocumentDB offers the tools and performance needed for efficient cloud storage, allowing businesses to grow and scale their cloud environment in the most optimal way possible.

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