Choose Cassandra when...

• •You need multi-cloud or hybrid-cloud portability and cannot accept vendor lock-in to a single cloud provider for your primary database.
• •Your workload requires extremely high write throughput with linear scalability, such as IoT telemetry ingestion, time-series data, or logging at millions of writes per second.
• •You need fine-grained tunable consistency per query, allowing different operations to trade latency for consistency based on their specific requirements.
• •Your data model benefits from Cassandra's wide-column design with collections, user-defined types, and materialized views for denormalized query patterns.
• •You have a dedicated database operations team with distributed systems expertise who can manage cluster operations, compaction strategies, and repair schedules.

Choose DynamoDB when...

• •You are building on AWS and want deep integration with the serverless ecosystem: Lambda triggers from DynamoDB Streams, API Gateway direct integration, and Step Functions orchestration.
• •Operational simplicity is your top priority and you do not want to manage database infrastructure, handle upgrades, tune JVM garbage collection, or schedule anti-entropy repairs.
• •Your traffic patterns are highly variable and you want on-demand capacity mode to automatically scale from zero to millions of requests per second without capacity planning.
• •Your team lacks distributed database operations expertise and you prefer to trade control for a fully managed service with built-in backups, encryption, and point-in-time recovery.
• •You need single-digit millisecond latency for key-value access patterns with DynamoDB Accelerator (DAX) providing microsecond-latency caching for read-heavy workloads.

Is DynamoDB faster than Cassandra?

For simple key-value lookups, both deliver single-digit millisecond latency. DynamoDB with DAX (DynamoDB Accelerator) can achieve microsecond-latency cached reads, which is faster than Cassandra's typical read path. However, Cassandra has no per-partition throughput limits, so it can sustain higher throughput on hot partitions. The practical performance difference depends on your access pattern, partition key design, and consistency level choices.

How much does it cost to operate Cassandra vs DynamoDB?

At steady, predictable workloads, self-managed Cassandra on reserved instances is typically 2-5x cheaper than DynamoDB provisioned mode for equivalent throughput. However, you must factor in the cost of database engineers ($150K-250K/year each) to operate Cassandra clusters. DynamoDB's on-demand mode eliminates capacity planning but costs roughly 6.5x more per unit than provisioned mode. For bursty workloads with long idle periods, DynamoDB on-demand is often cheaper because you pay nothing at rest.

Can I migrate from DynamoDB to Cassandra?

Yes, but the migration requires rethinking your data model. DynamoDB's partition key / sort key / GSI patterns map conceptually to Cassandra's partition key / clustering columns / materialized views, but the implementations differ. Tools like AWS DMS can export DynamoDB data, and DataStax provides migration utilities. The bigger challenge is rewriting application code to use CQL instead of the DynamoDB SDK and implementing the operational runbooks for Cassandra cluster management.

Which is better for time-series data?

Cassandra excels at time-series workloads due to its write-optimized LSM-tree storage engine, wide-column data model (partition by device ID, cluster by timestamp), and TTL-based automatic data expiration. DynamoDB can handle time-series data but requires careful partition design to avoid hot partitions (e.g., sharding by time bucket) and TTL for expiration. Companies like Netflix, Apple, and Discord use Cassandra for time-series workloads processing millions of writes per second.

How do Cassandra and DynamoDB handle multi-region?

Cassandra supports native multi-datacenter replication with NetworkTopologyStrategy, allowing you to place replicas in specific datacenters across any cloud or on-premises location with tunable consistency per datacenter. DynamoDB Global Tables replicate data across AWS regions with last-writer-wins conflict resolution and typically sub-second replication lag. Cassandra offers more control over conflict resolution and datacenter placement, while DynamoDB Global Tables are simpler to set up but limited to AWS regions.