S3 vs RDS vs DynamoDB — Choosing the Right AWS Storage for Your Data | DevOps Blogs | DevOps Network
S3 vs RDS vs DynamoDB — Choosing the Right AWS Storage for Your Data
S3 vs RDS vs DynamoDB — Choosing the Right AWS Storage for Your Data
Choosing S3, RDS, or DynamoDB wrong costs you in performance, cost, and scalability. Here is a practical decision guide based on your actual access patterns.
Frequently Asked Questions
Can you use DynamoDB for relational data that requires joins across multiple tables?
DynamoDB supports single-table design where data that would normally require joins is denormalised into one table using composite keys. This works well for known, fixed access patterns but becomes complex for ad-hoc querying. For data with genuinely relational structure and unpredictable query patterns, RDS or Aurora is the more maintainable choice.
What is the maximum object size in S3 and when must you use multipart upload?
The maximum S3 object size is 5 TB. Single PUT requests are limited to 5 GB, so any file above 5 GB must use multipart upload. AWS recommends multipart upload for files above 100 MB for better performance — it uploads parts in parallel and allows retry of individual failed parts rather than the entire file.
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