AWS- Types of Databases Explained

Data serves as the lifeblood of today’s businesses and applications. AWS Service, a prominent cloud service provider, presents many database solutions designed to meet the unique demands of contemporary enterprises. 

Now, what is the purpose of database systems?

Database systems are the cornerstone of modern cloud computing, powering many businesses and startups across various industries, from web hosting and e-commerce to artificial intelligence and big data analytics. AWS offers various database options, from the widely-used AWS Relational Database Service (RDS) to the high-performance DynamoDB. Each solution boasts distinct strengths and advantages, finely tuned to address specific use cases.

Dive in to learn about the uses of database systems and the characteristics of the different types of databases offered by the AWS database services.

What is Amazon Web Service (AWS)?

Amazon Web Services (AWS) is a comprehensive and widely used cloud computing platform offered by Amazon.com. The AWS service provides many cloud services and solutions, including computing power, storage, databases, machine learning, analytics, content delivery, and more. 

Database in AWS is designed to help businesses, organisations, and individuals build and manage scalable, flexible, and cost-effective IT infrastructures and applications. It operates data centres in multiple regions worldwide, allowing users to deploy resources close to their target audience for improved performance and reliability. 

Users can access these services on a pay-as-you-go basis, which means they only pay for the computing resources and services they use, making it a cost-effective option for a wide range of applications.

Advantages of Amazon Database Services

Amazon Web Services (AWS) offers different types of database systems. Here are some of the key advantages of using a database in AWS:

• Scalability for growing workloads: AWS database services quickly adapt to accommodate increased demands without disruptions.
• Managed services reduce admin tasks: AWS automates many database management functions, allowing your team to focus on application development.
• High availability and fault tolerance: Amazon AWS databases offer multiple availability zones and data replication to ensure continuous database access.
• Strong security and compliance features: AWS provides robust encryption, identity management, and compliance certifications for data protection.
• Performance optimisation options: AWS lets you choose the database type that matches your application’s performance needs.
• Global data centre reach for low latency: The global infrastructure offered by every AWS database type minimises latency by locating data centres near users.
• Cost-effective pay-as-you-go pricing: AWS charges only for the resources you use, reducing capital expenses.
• Automated backup and recovery: AWS offers automated backup solutions to avoid data loss in emergencies.
• Vast ecosystem and support: AWS provides a rich ecosystem of tools, services, and strong customer support.
• Seamless integration with AWS services: AWS databases seamlessly integrate with other AWS services, enhancing application functionality and efficiency.

Check out our free technology courses to get an edge over the competition.

Types of Amazon AWS Databases

Amazon Web Services (AWS) offers several database types for various data storage and processing needs. Each AWS database type is designed to address specific use cases, allowing users to choose the database that best suits their application’s requirements, whether for e-commerce, content management, real-time analytics, IoT, or other purposes.

Here is a comprehensive list of each AWS database type:

1. Key-Value Database  

A key-value database is a NoSQL database that stores and retrieves data as a collection of key-value pairs. Each data item in the database has a unique key, allowing fast and efficient data retrieval. Key-value databases are particularly well-suited for applications that require high-speed data access and can benefit from a simple data model.

Amazon DynamoDB

Amazon DynamoDB is a fully managed, highly available, and scalable NoSQL database application offered by the AWS service. It is designed to handle various use cases, from mobile and web applications to gaming, IoT, and more. DynamoDB stores data in a key-value format.

Benefits

Some of the benefits of NoSQL key-value databases like Amazon DynamoDB include:

• Scalable and fully managed NoSQL database
• Seamless and automatic scaling to handle any workload
• Low-latency performance suitable for high-demand applications 
• Integrated security and backup features

2. Relational Database  

A relational database management system (DBMS) organises data into structured tables with rows and columns. It uses a schema to define the structure of the data and the relationships between tables. 

A relational database service can handle complex queries and transactions, making it suitable for various applications, including business applications, e-commerce, and data-driven systems.

Amazon Aurora

Amazon Aurora is a fully managed relational database service offered by the AWS service. It is compatible with MySQL and PostgreSQL, offering high performance and availability.

Benefits

• High-performance, fully managed relational database
• Compatibility with MySQL and PostgreSQL
• Automatic replication for high availability and fault tolerance
• Scalability and performance enhancements

Amazon RDS

The AWS relational database service is a managed relational database service that supports various database engines, including MySQL, PostgreSQL, SQL Server, Oracle, and MariaDB. 

Benefits

• Managed relational databases for various engines (MySQL, PostgreSQL, SQL Server, Oracle, MariaDB)
• Automated backups and software patching
• Easy scalability to adjust resources as needed
• Enhanced security features

Amazon Redshift

Amazon Redshift is another fully managed data warehousing service designed for analytics and data warehousing. 

Benefits

• Fully managed data warehouse service
• High-performance analytics with massively parallel processing (MPP)
• Scalable and cost-effective for complex data queries
• Integration with popular BI tools

3. In-memory Database  

An in-memory database (IMDB) is a type of database management system that stores data primarily in the main memory (RAM) of a computer rather than on traditional disk storage devices such as hard drives or solid-state drives (SSDs). This approach allows for high-speed data access and retrieval because reading and writing data from memory is significantly faster than from disk.

Amazon ElastiCache

Amazon ElastiCache is an Amazon relational database service that is a fully managed in-memory data store service offered by the AWS service. It supports two popular in-memory engines: Redis and Memcached. 

Benefits

• Managed in-memory data store for caching and real-time applications.
• Support for Redis and Memcached engines.
• Enhanced application performance by reducing database load.
• Automatic data replication and failover.

Amazon MemoryDB for Redis

Amazon MemoryDB for Redis is a fully managed, Redis-compatible in-memory database service. It is designed for applications that require high throughput and low latency. 

Benefits

• A fully managed Redis-compatible in-memory database.
• Delivers sub-millisecond latency and high throughput.
• Suitable for use cases like gaming leaderboards, real-time analytics, and caching.
• Automatic failover and backup.

Check Out upGrad’s Software Development Courses to upskill yourself.

4. Document Database  

A document database also referred to as a document-oriented database, belongs to the category of NoSQL databases. Its purpose is to store, retrieve, and manage semi-structured or unstructured data. This is done in a manner that is flexible and doesn’t rely on a predefined schema.

Amazon DocumentDB (with MongoDB compatibility)

Amazon DocumentDB (with MongoDB compatibility) is a fully managed, document-oriented NoSQL database service provided by Amazon Web Services (AWS). It is compatible with the MongoDB API, making it easy for developers to transition from MongoDB to Amazon DocumentDB. 

Benefits

• Fully managed document database compatible with MongoDB.
• High availability with automatic backups and scaling.
• Secure, encrypted storage for sensitive data.
• Supports rich, flexible JSON-like document data models.

5. Wide Column Database  

A wide-column database is a NoSQL (Not Only SQL) database optimised for storing and retrieving large amounts of data with a schema that allows for flexibility in column-based data modelling. 

Amazon Keyspaces

Amazon Keyspaces is a fully managed, serverless, wide-columnar NoSQL database service provided by AWS. It is compatible with Apache Cassandra and designed for highly scalable applications. 

Benefits

• Serverless, fully managed wide-columnar NoSQL database.
• Compatible with Apache Cassandra.
• Automatically scales to accommodate varying workloads.
• Global distribution for low-latency access.

6. Graph Database  

A graph database is a database management system (DBMS) designed for efficiently storing, retrieving, and querying data structured as a graph. In a graph, data entities are represented as nodes (vertices), and the relationships between these entities are represented as edges (lines connecting the nodes). 

Graph databases excel at managing and traversing complex relationships and are particularly well-suited for applications involving highly interconnected data.

Amazon Neptune

Amazon Neptune is an AWS graph database service supporting property graph and RDF graph models. It is designed for applications requiring highly interconnected and complex data relationships. 

Benefits

• Fully managed graph database supporting property graph and RDF graph models.
• Enables building and querying highly connected data.
• Suitable for social networks, recommendation engines, and knowledge graphs.
• High availability and automated backups.

7. Time Series Database  

A time series database is a specialised database management system (DBMS) designed to efficiently store, manage, and query time-stamped or time-series data. Time series data consists of data points recorded at successive points, often at regular intervals. 

Amazon Timestream

Amazon Timestream is an AWS time series database, a purpose-built time-series database service provided by AWS. It is optimised for storing and querying time-series data generated by IoT devices, applications, and monitoring systems. 

Benefits

• Fully managed time-series database for IoT and operational data.
• Scalable and serverless architecture.
• Fast ingestion and querying of time-series data.
• Integration with analytics and visualisation tools.

8. Ledger Database  

A ledger database, specifically Amazon Quantum Ledger Database (Amazon QLDB), is a fully managed ledger database service provided by Amazon Web Services (AWS). It is designed to provide a secure, transparent, and immutable record of transactions and changes to data over time. 

Amazon Quantum Ledger Database (Amazon QLDB)

Amazon QLDB is a ledger database service provided and fully managed by AWS. It is designed for applications requiring an immutable and cryptographically verifiable transaction log. 

Benefits

• Fully managed ledger database with cryptographically verifiable transaction log.
• Immutable, tamper-evident data records.
• Suitable for applications requiring transparent and auditable data changes.
• Provides an immutable history of all changes to data.

Choosing A Suitable AWS Database

Choosing a suitable AWS database depends on various factors, including your application’s specific requirements, scalability needs, data model, and performance demands. Here are some considerations to help you select the right AWS database service:

• Data Model: Consider structured (RDS) or semi-structured/unstructured (NoSQL) data.
• Scalability: Choose DynamoDB for dynamic scaling or Aurora for growth.
• Performance: ElastiCache/MemoryDB for speed or Redshift for analytics.
• Data Analytics: Redshift for complex queries, Athena for S3 data.
• Graph Data: Neptune for interconnected data.
• Time-Series Data: Timestream for time-series data.
• Serverless: Aurora Serverless/DynamoDB On-Demand for auto-scaling.
• Data Integrity: Amazon QLDB for data integrity.
• Global Reach: DynamoDB Global Tables/Aurora Global Databases for global access.
• Management: Choose managed services for ease.
• Cost: Assess pricing alignment with your budget.
• Security: Ensure security and compliance.
• Migration: Evaluate the ease of migration.
• Support: Consider AWS support and community.
• Future Growth: Plan for scalability and future needs.

Conclusion

The primary purpose of database is to serve as a structured and organised repository for storing, managing, and retrieving data efficiently. Databases play a pivotal role in modern applications and businesses. Amazon Web Services (AWS) offers a diverse range of database services tailored to meet the unique needs of modern applications. 

Learning about various databases and understanding the options available when choosing an AWS database is crucial. It ensures that you select the proper database that aligns with your application’s performance, scalability, security, and budgetary needs, ultimately contributing to the success of your project.