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Amazon DynamoDB Complete Guide 2025: Architecture, Pricing ...
Excerpt
1. **Query flexibility**: The query model is limited to primary keys and secondary indexes. Complex joins, aggregations and full‑text search require other services (e.g., Elasticsearch or Redshift). Secondary indexes increase cost and require careful design. 2. **Item size limit**: A single item cannot exceed**400 KB**, which is much smaller than document databases like MongoDB (16 MB) or Cassandra (2 GB). Large objects should be stored in S3 and referenced from DynamoDB. 3. **Partition throughput limits**: Hot partitions can occur if the partition key isn’t sufficiently distributed, leading to throttling and increased latency. 4. **Vendor lock‑in**: DynamoDB runs exclusively on AWS. Migrating to other clouds or on‑premises systems requires rewriting applications or using compatible services. … ### Specific Technical Limitations Don’t use DynamoDB if you require: - Stored procedures or triggers - Complex nested data (beyond 32 levels) - Immediate global consistency (global tables have ~1s lag) - Backups older than 35 days - Exactly-once CDC (change data capture) … ### The “Red Flags” Checklist **Reconsider DynamoDB if you answer yes to any:** - Need queries by more than 5 attribute combinations? - Items regularly exceed 100KB? - Monthly AWS bill must stay under $100? - Require JOINs across multiple tables? - Must run outside AWS? - Need ACID across tables? - Frequent analytical queries required? - Need full-text search?
Related Pain Points
AWS vendor lock-in and service discontinuation risk
7AWS services can be discontinued or changed in breaking ways that force major application rewrites. Combined with deep vendor lock-in from using service-specific features, developers face long-term risk of forced refactoring or application unavailability.
Hot keys create single-node bottlenecks in Redis clusters
6Frequently accessed data that isn't distributed across multiple shards becomes a bottleneck, concentrating load on a single node. This defeats horizontal scaling benefits and creates performance ceiling for the application.
Backup and disaster recovery complexity at scale
6As data volume grows to terabytes and petabytes, teams struggle to establish robust backup and recovery systems that ensure zero data loss. The complexity of managing backups at scale, combined with the need for rapid recovery, creates operational burden and concerns about data durability.
No support for advanced relational features (JOINs, stored procedures, triggers)
6DynamoDB does not support SQL JOINs, stored procedures, triggers, or complex nested structures (beyond 32 levels). Applications requiring these features must implement logic in application code or use additional services, increasing complexity and performance overhead.
Single item size limit of 400KB
5DynamoDB enforces a hard 400KB limit per item, significantly smaller than competing document databases (MongoDB 16MB, Cassandra 2GB). Applications storing large objects must split data across items or use external storage like S3, adding architectural complexity.
No global consistency for distributed systems
4DynamoDB global tables introduce ~1 second replication lag, preventing immediate global consistency across regions. Applications requiring true ACID consistency across tables or regions cannot rely on DynamoDB.