What are the differences between Amazon Aurora and Amazon DynamoDB
Both are fully managed AWS database services, but they serve fundamentally different data models and access patterns. Aurora is a relational database for structured data with relationships; DynamoDB is a NoSQL key-value store built for single-digit millisecond performance at any scale.
Compare side-by-side
*Content generated by AI and reviewed for accuracy
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Comparisons
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Amazon Aurora
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Amazon DynamoDB
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Category
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Databases, Relational databases |
Databases, NoSQL databases, Non-relational databases |
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Description
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MySQL, PostgreSQL, and DSQL-compatible relational database designed for the cloud. Aurora PostgreSQL and Aurora MySQL are designed to deliver up to 6x the throughput of standard MySQL and PostgreSQL. Aurora DSQL provides serverless distributed SQL with active-active scaling to zero. |
Serverless, NoSQL, fully managed database designed for single-digit millisecond performance at any scale. |
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Best for
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Key features
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Pricing model
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On-Demand, Reserved, or Serverless (pay-per-use) |
On-demand or provisioned capacity |
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Free Tier
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Yes — Aurora DSQL and Aurora PostgreSQL |
Yes — 25GB + 25 read/write units |
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Expert take
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Aurora was designed for the cloud from the storage layer up. The result is MySQL/PostgreSQL/DSQL compatibility designed to deliver up to 6x the throughput, plus features like Global Database, serverless with scale to zero, vector database, and agent memory that don't exist in traditional engines. |
DynamoDB gives you single-digit millisecond reads and writes at any scale with zero operational overhead. The key is data modeling — when you design your access patterns upfront, DynamoDB rewards you with consistent performance that doesn't degrade as your table grows to petabytes. |
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Customer story
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View product pages
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How Aurora and DynamoDB compare
Both Amazon Aurora and Amazon DynamoDB are fully managed with encryption at rest and in transit, IAM integration, automated backups, and point-in-time recovery. The features listed in the table above highlight where the services differ.
Choose Aurora when your data has relationships (foreign keys, joins), you need complex queries (aggregations, subqueries, ad-hoc reporting), or your team is most productive with SQL. Aurora excels at transactional workloads where data consistency and relational integrity matter.
Choose DynamoDB when you know your access patterns upfront, need predictable single-digit millisecond latency at any scale, or want zero operational overhead. DynamoDB excels at high-throughput, key-value workloads where you trade query flexibility for performance and scalability.
Common pattern: Many architectures use both — DynamoDB for the hot path (session stores, user profiles, real-time feeds) and Aurora for the analytical path (reporting, complex queries, data that needs joins).
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