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AWS Database Services: Complete Guide

Last Updated : 05 Feb, 2024
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AWS Database Services is a group of cloud-based services offered by Amazon Web Services (AWS). These services help businesses and developers manage, process, and analyze their data efficiently and securely. Amazon Web Services (AWS) offers a variety of database services to cater to different application needs. These services are designed to be scalable, reliable, and cost-effective.

What Are The AWS Databases?

A database is an electronically stored, systematic collection of data. It can contain any type of data, including words, numbers, images, videos, and files. You can use software called a database management system (DBMS) to store, retrieve, and edit data. In computer systems, the word database can also refer to any DBMS, to the database system, or to an application associated with the database.

AWS databases are a set of managed database services supplied by Amazon Web Services that are intended to provide dependable, scalable, and secure database solutions for a variety of use cases. These services include Amazon RDS for relational databases, Amazon DynamoDB for NoSQL databases, Amazon Redshift for data warehousing, and Amazon ElastiCache for in-memory caching, among others. AWS databases include capabilities such as automatic backups, patching, and fast setup, allowing enterprises to focus on application development while AWS manages the database.

Comparison Between Different Types Of Databases

Database Type


AWS Services


customer relationship management(CRM), e-commerce, Online Transaction Processing (OLTP) applications

Amazon Aurora, Amazon RDS, Amazon Redshift


Internet of Things (IoT), ecommerce systems, Web applications

Amazon DynamoDB


geospatial applications, gaming leaderboards, caching

Amazon ElastiCache, Amazon MemoryDB for Redis


content management systems, e-commerce platforms, user profiles

Amazon DocumentDB (with MongoDB compatibility)

Wide column

fleet management, route optimization, High-scale industrial applications

Amazon Keyspaces


Social networks, recommendation engines, fraud detection, and network security applications.

Amazon Neptune

Time series

Industrial telemetry, DevOps, IOT applications

Amazon Timestream


Supply chain tracking, financial transactions, and regulatory compliance applications.

Amazon Quantum Ledger Database Services (QLDB)

Types Of Databases

Amazon’s database includes various types of data warehouses. Here’s a quick glossary to explain the differences between these popular database categories:

  1. Relational database: Relational databases store data in tables with columns and rows, with each row representing a single record, differentiated with a unique ID known as a key, and each column containing data related to that record. Relational databases have been around since the 1970s and are now the most commonly used type of data warehouse. Many relational databases are managed using the programming language SQL.
  2. Key-value database: Key-value databases are non-relational databases that use a basic key-value method to store data. Data is warehoused in key-value pairs; each key serves as a unique identifier for a single value within the collection. This works in a similar way to a dictionary: the word is the key, and the definition is the value.
  3. In-memory database: In-memory databases are non-relational databases that rely on memory for data storage, making queries faster by eliminating the need to access disks.
  4. Document database: They offer flexible, semi-structured, hierarchical storage for use cases like catalogs and user profiles, and content management systems such as blogs and video platforms.
  5. Wide column database: These are NoSQL databases that use tables, rows, and columns like usual, but unlike a relational database, column names and formats can vary row to row.
  6. Graph database: Graph databases store data not in tables, but in an interconnected web-like structure that allows complex relationships between data to be mapped and queried.
  7. Time-series database: These are designed to store and retrieve data points that are associated with timestamps.
  8. Ledger databases: This databases contain both tables of data and an immutable journal that logs all changes to data, creating a blockchain record of all updates.

Types Of AWS Database Services

As stated previously, AWS provides a variety of relational and non-relational databases as cloud services for users. Given below is a list of these database services.

1. Amazon Aurora

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud. It offers high performance, reliability, and scalability with features like automatic replication across multiple Availability Zones. Typically up to five times faster than standard MySQL databases, it’s also compatible with PostgreSQL, and is up to three times quicker than standard PostgreSQL options.

Aurora databases are fully managed by AWS’s Relational Database Service (RDS), meaning all administrative work is taken care of at the vendor’s end. Aurora stores data in 10GB “chunks”; and if you need to increase the size of your Aurora database, it automatically scales up in 10GB increments, up to a maximum capacity of 64TB.

Aurora databases are created within an Amazon Virtual Private Cloud (VPC), so users can quarantine a database for use solely within their network for extra security if necessary. Plus, all network keys are user-assigned and can be managed with the AWS Key Management Service.

Data stored in an Aurora database is replicated six times across three Availability Zones (AZs) to make sure your data is always available when you need it. If any corruption occurs, the database self-heals by pulling the copied data back into the main database. Data is continuously backed up to Amazon’s S3 storage platform.

Features of Amazon Aurora

  • It is a highly scalable managed database service that has a high throughput when compared to other databases.
  • Services are both long-lasting and readily available.
  • Read replicas help to scale read operations.
  • Aurora is serverless, allowing for automatic scalability based on demand.
  • Global databases provide cross-region replication.

2. Amazon RDS

Amazon RDS is a managed relational database service that supports several database engines, including MySQL, PostgreSQL, MariaDB, Oracle, and Microsoft SQL Server. That means you get all the benefits of Amazon RDS while still being able to stick with database engines you’re already familiar with—kind of like hiring a butler to work in a house you already own. It automates routine administrative tasks such as backups, patch management, and database scaling.

It frees you to focus on your applications so you can give them the fast performance, high availability, security and compatibility they need. You can use the AWS Database Migration Service to easily migrate or replicate your existing databases to Amazon RDS.

Features of Amazon RDS

  • It is a highly scalable Relational DBMS that enables excellent performance in the infrastructure.
  • Auto backup and restore features improve the consistency and durability of consumer data.
  • Read replicas for read scaling.
  • Support for many database engines.
  • Integration with AWS CloudWatch for monitoring.

3. Amazon Redshift

Amazon Redshift is also a managed database service and a relational database, running its own engine adapted from PostgreSQL. It can be more costly, more complex to work with and much more powerful.

Amazon Redshift is the most popular AWS database, hosting more than 15,000 active customers. Businesses using Redshift include Lyft, McDonalds, and Philips, but that’s not to say it’s only suited to enterprise businesses; its high performance and scalability mean it’s a good choice for any kind of business with mission-critical analytical workloads.

Each Amazon Redshift data warehouse is made up of a collection of computing resources known as nodes. These groups of nodes as called clusters. Nodes are available in different sizes, depending on the total storage capacity you need, and the complexity of your queries. Redshift can be scaled up or down with just a few clicks if you need to add more nodes.

All other admin factors, like data backups, upgrades, and patches, are taken care of at AWS’s end.

Features of Amazon Redshift

  • Allows us to execute queries in parallel across several system nodes.
  • Provision of auto-Backup on Amazon S3.
  • It is less expensive than other competitive data warehouse services.
  • Built-in security features include end-to-end encryption and user-configurable firewall restrictions.
  • Integration with key business intelligence tools.

4. Amazon DynamoDB

Amazon DynamoDB is a fully managed NoSQL database service that provides seamless scalability and low-latency performance. It is suitable for applications that require high throughput and low-latency responses. It’s an extremely powerful platform for querying data, able to handle more than 10 trillion requests per day, at peaks of more than 20 million requests per second.

Many of the world’s fastest growing businesses such as Lyft, Airbnb, and Redfin, as well as enterprises such as Samsung, Toyota, and Capital One, depend on the scale and performance of DynamoDB to support their mission-critical workloads.

Thousands of people have chosen DynamoDB as their key-value and document database for mobile, web, gaming, Internet of Things (IoT), and other applications that need low-latency data access at any scale. Create a new table for your application and let DynamoDB handle the rest.

Features of Amazon DynamoDB

  • Allows us to run queries in parallel on many system nodes.
  • Automatic backup on Amazon S3.
  • It is less expensive than comparable data warehousing services.
  • End-to-end encryption and user-configurable firewall limits are among the security features included by default.
  • Integration of major business intelligence technologies.

5. Amazon ElastiCache

Amazon ElastiCache is a fully managed, in-memory caching service that supports popular open-source caching engines such as Redis and Memcached. It is used to improve the performance of applications by caching frequently accessed data.

ElastiCache offers a platform for the speedy retrieval of information managed, in-memory system, eliminating the need to rely on disk-based databases. Like AWS’s other database services, ElastiCache is fully managed, removing the burden of patching, provisioning, and recovery for users.

It will also come in handy as primary data for applications where data durability is not a priority.

Features of Amazon ElastiCache

  • Elasticache’s ability to extract data from an in-memory system reduces response time significantly.
  • Integration of prominent programming languages.
  • Fully managed services, which means that all administrative chores (backup and recovery, provisioning, etc.) are automated.
  • Support for clustering and replication.

6. Amazon MemoryDB for Redis

Amazon MemoryDB for Redis is a durable, in-memory database service for ultra-fast performance. Amazon MemoryDB for Redis is a cloud-based, fully managed in-memory database service that is compatible with the popular open-source Redis database. Redis is known for its high performance, simplicity, and versatility, making it widely used for caching, session storage, real-time analytics, and other use cases requiring fast data access.

MemoryDB for Redis is designed to provide a seamless and compatible experience for Redis users while offloading the operational burden associated with managing and maintaining the underlying infrastructure. The service is suitable for a wide range of applications where low-latency data access and high-throughput are critical.

Delivering both in-memory performance and Multi-AZ durability, MemoryDB can be used as a high-performance primary database for your microservices applications eliminating the need to separately manage both a cache and durable database.

Features of Amazon MemoryDB

  • Backups are performed on a continuous, automatic basis to ensure data durability.
  • Optimized for fast in-memory data access.
  • Encryption during transit and at rest, VPC support, and IAM integration.
  • Horizontal scaling, with the option to add or delete shards.

7. Amazon DocumentDB (with MongoDB compatability)

Amazon DocumentDB is a managed document database service that is compatible with MongoDB. It provides the scalability and performance of a NoSQL database while preserving the flexibility and power of MongoDB.

Developers can use the same app code, drivers, and tools to run and manage workloads on DocumentDB, enjoying all of the improved performance and scalability that comes with it without having to deal with MongoDB infrastructure.

Amazon DocumentDB offers twice the throughput of MongoDB managed services, and splits up compute and storage so both aspects can scale independently to meet individual needs. DocumentDB comes with all the bells and whistles you’d expect from an AWS database; high availability, durability, security, and auto-scaling.

Features of Amazon DocumentDB

  • Scalable and distributed architecture.
  • Completely managed service.
  • Compatible with current MongoDB apps.
  • Automatic backups and snapshots.

8. Amazon Keyspaces

Amazon Keyspaces is a fully managed, serverless, and highly available Apache Cassandra-compatible database service provided by AWS. Cassandra is a popular NoSQL database known for its ability to handle massive amounts of data with high scalability and performance.

Amazon Keyspaces is designed to simplify the management and operation of Cassandra databases by offloading administrative tasks and providing seamless integration with AWS services.

You can build applications that serve thousands of requests per second with virtually unlimited throughput and storage. Data is encrypted by default and Amazon Keyspaces enables you to back up your table data continuously using point-in-time recovery.

Features of Amazon Keyspaces

  • Automatically scales resources to meet demand.
  • Data is replicated across multiple availability zones to ensure fault tolerance.
  • A cost-effective methodology based on read and write requests and storage use.
  • Supports current Cassandra Query Language (CQL) queries and drivers.

9. Amazon Neptune

Amazon Neptune is a fully managed graph database service that allows you to build and run applications with highly connected datasets, such as social networks and recommendation engines. Amazon Neptune is highly available, with read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across Availability Zones.

Neptune makes it straightforward for businesses to take advantage of highly connected datasets, and supports popular graph query languages to pull relationship data with millisecond latency. Like Aurora, Neptune duplicates data six times across three AZs, in 10 GB segments.

Neptune is secure with support for encryption at rest. Neptune is fully-managed, so you no longer need to worry about database management tasks such as hardware provisioning, software patching, setup, configuration, or backups.

Features Of Amazon Neptune

  • Support for both property graph and RDF graph models.
  • High availability, including automatic backups.
  • Multi-AZ deployments improve reliability.
  • Secure and compliant.

10. Amazon Timestream

Amazon Timestream is a fast, scalable, fully managed time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day at 1/10th the cost of relational databases.

With Timestream, you can easily store and analyze log data for DevOps, sensor data for IoT applications, and industrial telemetry data for equipment maintenance. As your data grows over time, the Timestream adaptive query processing engine understands its location and format, making your data simpler and faster to analyze.

It comes with built-in analytical functions too, like smoothing, approximation, and interpolation. Timestream’s adaptive query processing engine means the databases gets smarter over time, making analysis of your data even faster. It also self-manages rollups, retention, tiering, and data compression to make sure you’re only using the capacity you need.

Features Of Amazon Timestream

  • Automatically scaled for high-volume time-series data.
  • Includes time-series-specific utilities to facilitate data handling.
  • Supports in-memory analytics for quick queries.
  • Designed for efficient storage and querying of time-series data.
  • It seamlessly connects with AWS IoT services.

11. Amazon Quantum Ledger Database (QLBD)

The newest edition to Amazon’s database stable, Amazon Quantum Ledger Database is a centralized blockchain service, providing users with an absolute, cryptographically verifiable log. Amazon QLDB creates permanent, unchangeable records of transactions, and can be used to store data for apps that require centralized, trusted authority.

With QLDB, your data’s change history is immutable – it cannot be altered or deleted – and using cryptography, you can easily verify that there have been no unintended modifications to your application’s data. QLDB uses an immutable transactional log, known as a journal, that tracks each application data change and maintains a complete and verifiable history of changes over time.

QLDB is easy to use because it provides developers with a familiar SQL-like API, a flexible document data model, and full support for transactions. QLDB is also serverless, so it automatically scales to support the demands of your application.

Features Of Quantum Ledger Database

  • Transactions are made more transparent and cryptographically verified.
  • With a serverless design, resources are automatically scaled in response to demand.
  • Integrates well with other AWS services to enable complete application development.
  • Eliminates the requirement for ledger maintenance chores, lowering the operating strain.
  • Creates an immutable and tamper-proof transaction log.

Advantages of Amazon AWS Databases

  1. Fully Managed: AWS Database services are fully managed services that relieve many of the setup, management, and monitoring responsibilities off of the business’s shoulders.
  2. Scalable: AWS provides a set of Databases that are highly scalable when compared to popular alternative databases. This is true for both the relational and non-relational databases provisioned by AWS.
  3. Highly available: Given its global infrastructure setup and fault tolerance mechanism, AWS provides highly available and reliable services across the globe.
  4. Security: Provides highly secure services due to the implementation of multi-level security systems like network isolation and end-to-end encryption.


In conclusion, Amazon Web Services (AWS) offers a comprehensive suite of database services that cater to diverse business needs, providing scalable, reliable, and cost-effective solutions. The range of database options available on AWS, including relational, NoSQL, in-memory, and purpose-built databases, allows organizations to choose the most suitable platform for their specific requirements.

The cloud-native nature of these services enables businesses to focus on innovation and application development rather than infrastructure management.

AWS Database Services – FAQ’s

How Does AWS Backup Work For Databases?

AWS Backup is a centralized backup service that simplifies the process of backing up data across AWS services, including databases. It enables automated and policy-based backups, making it easier to manage backup and restore processes.

How Is Data Migration Handled In AWS Database Services?

AWS provides services like AWS Database Migration Service (DMS) to simplify the process of migrating databases to and from the AWS Cloud. It supports homogeneous and heterogeneous migrations between different database engines.

How Does Amazon ElastiCache Enhance Database Performance?

Amazon ElastiCache provides in-memory caching to reduce the load on databases. By storing frequently accessed data in a cache, ElastiCache improves query response times and overall application performance.

How Can I Scale My Database On Amazon RDS?

To address rising workloads, Amazon RDS enables both vertical scaling (resizing instance types) and horizontal scaling (read replicas).

How Does Amazon CloudWatch Work With AWS Databases?

Amazon CloudWatch monitors and logs AWS resources, including databases. You can use CloudWatch metrics and alerts to track the performance of your databases.

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