vs

Amazon Aurora vs Amazon Aurora DSQL

Amazon Aurora: AWS's MySQL- and PostgreSQL-compatible engine on a shared, six-way replicated storage layer. Amazon Aurora DSQL: Serverless, active-active distributed SQL on AWS with PostgreSQL compatibility and no instances to size.

key differences

  • Horizontal scaling is addon in Amazon Aurora and native in Amazon Aurora DSQL.
  • Only Amazon Aurora has full-text search, vector search, geospatial, json, change data capture.
  • Only Amazon Aurora DSQL has compression, online schema changes.

choose amazon-aurora for

  • +Production MySQL or PostgreSQL backends on AWS
  • +Read-heavy web and SaaS applications
  • +Spiky or dev/test workloads on Serverless v2
  • +Cross-region disaster recovery with Global Database

best at · OLTP, Content, Metadata

choose amazon-aurora-dsql for

  • +New AWS-native microservices needing zero-ops relational storage
  • +Multi-Region active-active user, order and entitlement data
  • +Serverless apps on Lambda with spiky traffic
  • +Ledgers and counters that must never lose a committed write

best at · OLTP, Metadata, Ledger

overview
Primary model
Relational
Relational
Also supports
Document, Spatial, Vector
–
Type
Managed service
Managed service
Status
Active
Active
Developer
Amazon Web Services
Amazon Web Services
First release
2015
2025
Latest version
–
–
License
ProprietaryProprietary (AWS service)
ProprietaryProprietary (AWS service)
Free tier
—
✓
popularity
WhichDB Score
24.9
14.7
Rank
#123
#227
GitHub stars
–
–
Stack Overflow questions
1.6K
1
scale & guarantees
Comfortable data size
Large (≤ 1 PB)
Large (≤ 1 PB)
Horizontal scaling
Addon
Native
Multi-region
Read replicas
Active active
ACID
Full
Full
Consistency
Strong, Eventual
Strong
Schema
Strict
Strict
Architecture
Shared storage, Primary replica, Serverless
Distributed, Serverless, Multi primary
deployment
Self-hosted
—
—
Vendor-managed cloud
✓
✓
Serverless
✓
✓
Embedded
—
—
Edge
—
—
Clouds
AWS
AWS
capabilities
Transactions
✓
✓
Joins
✓
✓
Secondary indexes
✓
✓
Full-text search
✓
—
Vector search
✓
—
Geospatial
✓
—
JSON
✓
—
Change data capture
✓
—
Triggers
✓
—
Stored procedures
✓
—
Materialized views
✓
—
TTL / expiry
—
—
Pub/Sub
✓
—
Columnar storage
—
—
In-memory
—
—
Durable persistence
✓
✓
Compression
—
✓
Encryption at rest
✓
✓
Role-based access
✓
✓
Time travel
✓
—
Branching
✓
—
Online schema changes
—
✓
Streaming ingest
—
—
Offline sync
—
—
Runs in WebAssembly
—
—
interfaces
Query languages
SQL, PL/pgSQL
SQL
Client languages
Java, Python, JavaScript, Go, C#, PHP, Ruby
Java, Python, JavaScript, Go, Rust, C#, Ruby
Best for
OLTP, Content, Metadata, Vector search
OLTP, Metadata, Ledger

Amazon Aurora vs Amazon Aurora DSQL: FAQ

What is the difference between Amazon Aurora and Amazon Aurora DSQL?

Amazon Aurora: AWS's MySQL- and PostgreSQL-compatible engine on a shared, six-way replicated storage layer. Amazon Aurora DSQL: Serverless, active-active distributed SQL on AWS with PostgreSQL compatibility and no instances to size. Horizontal scaling is addon in Amazon Aurora and native in Amazon Aurora DSQL. Only Amazon Aurora has full-text search, vector search, geospatial, json, change data capture. Only Amazon Aurora DSQL has compression, online schema changes.

When should I choose Amazon Aurora over Amazon Aurora DSQL?

Choose Amazon Aurora for production MySQL or PostgreSQL backends on AWS; read-heavy web and SaaS applications; and spiky or dev/test workloads on Serverless v2. Choose Amazon Aurora DSQL for new AWS-native microservices needing zero-ops relational storage; multi-Region active-active user, order and entitlement data; and serverless apps on Lambda with spiky traffic.

Is Amazon Aurora or Amazon Aurora DSQL more popular?

Amazon Aurora ranks #123 on the WhichDB Score (24.9/100) and Amazon Aurora DSQL ranks #227 (14.7/100). Popularity is not fit: check the requirements that matter for your project.

Are Amazon Aurora and Amazon Aurora DSQL open source?

No. Amazon Aurora is proprietary, closed-source software. No. Amazon Aurora DSQL is proprietary, closed-source software.