Choose the Right Database
Learning Objectives
After completing this unit, you’ll be able to:
- Differentiate between AWS database services.
- Choose the right database service for your use case.
Meet the Challenges of Today’s Data
Modern data requirements can be challenging. Scaling for millions of users, maintaining accessibility across the globe, and ensuring a millisecond response time for a strong customer experience are just a few of the things you have to consider.
The data itself has changed as well. Today’s data often comes at high speeds, in high volumes, and with strange formats and structures that are incompatible with traditional schemas.
Beyond Relational Databases
There’s a saying that goes, “If all you have is a hammer, everything looks like a nail.” The same can be said for relational databases: “If all you have is a relational database, everything looks like a schema.” But in the real world, you have a wide variety of tools that aren’t hammers, and a wide variety of databases that aren’t relational databases.
You have more choices of databases that go beyond relational, such as key-pair, graph, document, and ledger databases. These databases were built with today’s data and data requirements in mind.
AWS Database Services
AWS has a variety of different database options for different use cases. Use the table below to get a quick look at the AWS database portfolio.
| Database Type | Use Cases | AWS Service |
|---|---|---|
|
Relational |
Traditional applications, ERP, CRM, e-commerce |
Amazon RDS, Amazon Aurora, Amazon Redshift |
|
Key-value |
High-traffic web apps, e-commerce systems, gaming applications |
Amazon DynamoDB |
|
In-memory |
Caching, session management, gaming leaderboards, geospatial applications |
Amazon ElastiCache for Memcached, Amazon ElastiCache for Redis |
|
Document |
Content management, catalogs, user profiles |
Amazon DocumentDB (with MongoDB compatibility) |
|
Wide column |
High-scale industrial apps for equipment maintenance, fleet management, and route optimization |
Amazon Keyspaces (for Apache Cassandra) |
|
Graph |
Fraud detection, social networking, recommendation engines |
Amazon Neptune |
|
Time series |
IoT applications, DevOps, industrial telemetry |
Amazon Timestream |
|
Ledger |
Systems of record, supply chain, registrations, banking transactions |
Amazon QLDB |
Breaking Up Applications and Databases
As the industry changes, applications and databases change too. Today, with larger applications, you no longer see just one database supporting it. Instead, these applications are being broken into smaller services, each with their own purpose-built database supporting it.
This shift removes the idea of a one-size-fits-all database and replaces it with a complimentary database strategy. You can give each database the appropriate functionality, performance, and scale that the workload requires.
Wrap Up
For smaller applications, like your cat photo application, it makes sense to have only one database. However, the larger the application gets, you may need to develop a database strategy and have several different databases supporting the workload. In the next module, you learn how to monitor and troubleshoot your applications.