Can I use joins in DynamoDB like I can in RDS?

Not in the way relational databases support them. DynamoDB is designed around retrieving items by key rather than joining across tables, so related data is typically modelled differently — often denormalised into the item itself — rather than joined at query time.

Which one should a beginner learn first?

RDS and standard SQL are usually the more familiar starting point, since relational concepts (tables, joins, transactions) are widely taught. DynamoDB is worth learning once you understand why access-pattern-driven NoSQL design differs from relational modelling.

Does DynamoDB support transactions at all?

Yes, DynamoDB supports transactions across multiple items, but the natural and most scalable pattern in DynamoDB favours operations on a single item or partition rather than the broad multi-table transactions relational databases are built around.

Do I have to choose only one database for my whole application?

No. It is common to use RDS for structured, relational business data and DynamoDB for a specific high-scale or access-pattern-driven part of the same system — the choice is made per workload, not once for the entire application.

Cloud basics

RDS vs DynamoDB: which AWS database should you use?

By the SaveMyCert Editorial TeamPublished 10 Sept 2026Updated 10 Sept 2026

Amazon RDS is a managed relational (SQL) database for structured, related data with joins and transactions, while Amazon DynamoDB is a managed NoSQL key-value and document database built for massive scale and predictable access patterns — the choice is driven by your data model, not by which service is "better". Both remove the operational burden of running a database server yourself, but they solve different problems underneath that shared convenience. This guide explains what each service actually is, lays out the differences that matter when picking one, and gives an honest view of when a real system ends up using both rather than treating the decision as one-or-the-other.

What each service is

Our what is Amazon RDS explainer covers the service in depth; in short, RDS runs standard relational database engines for you and manages patching, backups and failover. Our what is Amazon DynamoDB explainer covers that service in depth too; in short, DynamoDB is a fully managed NoSQL database that stores items as key-value pairs or documents and scales without you provisioning database servers at all. The deeper concept behind the choice — relational versus NoSQL data modelling — is covered in relational vs NoSQL databases, which this comparison builds on rather than repeats.

The key differences

The two services differ in ways that matter well before you write a single query:

Data model — RDS stores data in tables with defined schemas and relationships between them; DynamoDB stores independent items, typically without joins across tables.
Scaling — RDS scales primarily by resizing a database instance (and read replicas for read-heavy loads); DynamoDB scales horizontally and is designed to handle very large, unpredictable workloads without manual resizing.
Query flexibility vs access-pattern design — RDS lets you write ad-hoc SQL queries and joins after the fact; DynamoDB expects you to design your keys and access patterns up front, around the specific ways you will read the data.
Consistency and transactions — RDS engines are built around strong consistency and multi-table transactions as a default; DynamoDB supports transactions too, but the natural pattern favours single-item or single-partition operations at scale.
Typical uses — RDS suits applications with genuinely relational data (orders linked to customers linked to products); DynamoDB suits applications needing predictable low-latency access at very high scale, such as session stores, shopping carts or IoT data.

When to choose RDS

Choose RDS when your data is naturally relational — records that reference each other and benefit from joins, and workloads where you need flexible, ad-hoc querying that was not fully anticipated when you designed the schema. RDS also suits teams migrating an existing relational application, or ones who value SQL and the maturity of tools built around it, over reworking the whole model around a different paradigm.

When to choose DynamoDB

Choose DynamoDB when you know your access patterns in advance and need consistent, low-latency performance regardless of how large the dataset grows, without managing or resizing servers. It fits well where the data is naturally item-shaped — a user profile, a cart, a device reading — rather than a web of related tables, and where the scale or unpredictability of traffic would make managing a relational instance harder work than it is worth.

Not always either/or

Many real systems use both: a relational database such as RDS for the core, structured business data that benefits from joins and transactions, and DynamoDB alongside it for a specific high-scale, access-pattern-driven workload such as session storage or an event feed. The decision is per-workload, not per-application — picking RDS for one part of a system does not commit you to it everywhere, and the same applies in reverse.

Where this appears in cert study

Choosing between relational and NoSQL storage, and specifically between RDS and DynamoDB, is core material in the Solutions Architect Associate and Developer Associate exams, and features again in the Data Engineer Associate, which goes deeper into modelling data for each.

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Questions, answered

They are optimised for different things rather than one being simply faster. DynamoDB is designed for consistent, predictable low-latency access at very high scale once your access patterns are fixed; RDS is optimised for flexible relational querying, which is a different job.