DynamoDB vs Amazon RDS
DynamoDB and Amazon RDS are both managed AWS databases, but they represent two different worlds. DynamoDB is a serverless NoSQL key-value and document database designed around known access patterns and horizontal scale. Amazon RDS is a managed service for running instance-based relational engines — MySQL, PostgreSQL, MariaDB, SQL Server, Oracle, and Db2 — with full SQL, joins, and enforced schemas.
Should you use DynamoDB or RDS?
Choose DynamoDB for high-scale operational workloads with predictable, key-based access where you want serverless scaling and no instances to manage. Choose Amazon RDS when you need full SQL — joins, ad-hoc queries, transactions across normalized tables — on a familiar relational engine and your data fits an instance you can vertically scale with read replicas. Query flexibility versus hands-off scale is the core trade.
DynamoDB vs Amazon RDS at a glance
| Characteristic | DynamoDB | Amazon RDS |
|---|---|---|
| Data model | NoSQL key-value and document; flexible per-item schema, items up to 400 KB | Relational — tables, rows, and columns with an enforced schema, on your chosen engine |
| Query language | Native API (GetItem, Query, Scan) plus PartiQL, a SQL-compatible language | Full SQL of the underlying engine (MySQL, PostgreSQL, MariaDB, SQL Server, Oracle, Db2) |
| Joins & relations | No JOIN operator; AWS recommends denormalizing around access patterns | Full relational joins, foreign keys, and constraints across tables |
| Indexes | Global and local secondary indexes on an alternate key | The engine's index types (B-tree, hash, and engine-specific), plus partial/expression indexes on some engines |
| Consistency | Eventually consistent by default; strongly consistent reads per request; ACID transactions | Strong consistency by default; full multi-statement ACID transactions |
| Scaling model | Horizontal — automatic partitioning; serverless on-demand scales up and down (to zero) | Vertical — a provisioned instance you resize, plus read replicas for read scale-out |
| Provisioning / ops | Serverless; no instances to size or patch | Instance-based; you pick class and storage, AWS manages patching, backups, and failover (Multi-AZ optional) |
| Pricing model | Pay-per-request (on-demand) or provisioned capacity plus storage; scales to zero when idle | Instance-hours for the DB class plus storage (and I/O on some options), billed while the instance runs |
| Best-fit workloads | High-scale operational apps with known key access (carts, sessions, events, leaderboards) | Relational and analytical workloads needing joins, ad-hoc queries, and strong data integrity |
When DynamoDB is the better choice
- Your access patterns are known and key-based. Designing keys around your reads gives consistent single-digit-millisecond latency whether you have hundreds or hundreds of millions of users.
- You want serverless with no instances. On-demand capacity has nothing to size or patch and scales to zero when idle — no instance running around the clock.
- You need to scale writes horizontally. DynamoDB partitions automatically; you do not add sharding tooling as you would to scale a single relational primary.
- Your workload is item-oriented (profiles, sessions, carts, events) rather than a web of joined tables.
When Amazon RDS is the better choice
- You need full SQL and joins. RDS runs real relational engines with joins, aggregations, foreign keys, and ad-hoc queries across normalized tables.
- Your access patterns keep evolving. A relational schema with flexible querying adapts to new questions without redesigning keys.
- You want a familiar engine. MySQL, PostgreSQL, MariaDB, SQL Server, Oracle, and Db2 let teams reuse existing skills, tools, and SQL.
- Your dataset fits a vertically scaled instance with read replicas, and steady query-heavy traffic suits an always-on instance.
Working with DynamoDB
If DynamoDB is the right side of the split, DynoTable is a native desktop client for it on macOS, Windows, and Linux. It reads your standard AWS credential chain, so your data stays in DynamoDB with nothing to migrate. Crucially for teams coming from RDS, its SQL Workbench expresses relational-shaped queries — joins, GROUP BY, aggregates — within DynamoDB's access-pattern rules by compiling them down to DynamoDB's own Query/Scan operations, and its AI assistant runs on your own AWS Bedrock credentials.
If you miss writing SQL, the SQL for DynamoDB and PartiQL vs SQL guides explain what maps across and what does not, and the DynamoDB JOIN guide covers modeling relationships without a native join. The free DynamoDB Expression Builder generates correct key conditions, filters, and update expressions in SDK, CLI, and PartiQL form. DynoTable is a closed-source commercial app; this page describes what it does, not how it is built.
FAQ
Can DynamoDB replace Amazon RDS?
For some workloads, yes. If your access patterns are predictable and key-based, DynamoDB can replace an RDS instance and remove most scaling and patching work. It is a poor fit where you rely on joins, ad-hoc relational queries, or a constantly changing query surface — RDS's strengths. Many teams run both: RDS for relational work, DynamoDB for high-throughput key access.
Does DynamoDB support SQL and joins like RDS?
DynamoDB supports PartiQL — a SQL-compatible language for SELECT, INSERT, UPDATE, and DELETE — but it has no JOIN operator; AWS recommends denormalizing instead. The engines behind RDS support full SQL including joins across tables. See Joins in DynamoDB for how to model relationships without one.
Is DynamoDB cheaper than RDS?
It depends on the workload, so model both. DynamoDB bills per request (or provisioned capacity) plus storage and scales to zero when idle, which suits spiky or low-baseline traffic. RDS bills instance-hours for a running class plus storage, which can be more cost-effective for steady, query-heavy workloads. Estimate against your real access patterns before deciding.
Related
- Learn SQL for DynamoDB, PartiQL vs SQL, and joins in DynamoDB.
- Model data around access patterns with how to model data in DynamoDB.
- Build queries fast with the free DynamoDB Expression Builder.
- Download DynoTable for macOS, Windows, or Linux.
Last verified 2026-07-12 against the official AWS DynamoDB and Amazon RDS documentation. Amazon RDS and DynamoDB are services of Amazon Web Services; referenced here for identification only.