Cassandra vs. DynamoDB

by walter

Table of Contents

Cassandra and DynamoDB are both distributed NoSQL databases, but they have key differences in architecture, scalability, and use cases. Here's a detailed comparison:

1. Architecture

Feature Cassandra DynamoDB
Model Open-source, decentralized, peer-to-peer Managed, serverless, centralized with regional replication
Consistency Tunable consistency (can be strong or eventual) Strong or eventual consistency per request
Replication Multi-datacenter replication supported AWS-native cross-region replication
Partitioning Consistent hashing with virtual nodes (vnodes) Partitioned by AWS internal mechanisms

2. Scalability & Performance

Feature Cassandra DynamoDB
Scaling Scales horizontally by adding nodes Fully managed auto-scaling
Read/Write Performance High throughput with tunable read/write consistency Predictable latency with automatic scaling
Storage Model Append-only log-structured storage SSD-backed, automatically optimized
Hot Partitions Can suffer from hot partitions if data is not well distributed Can have throttling issues on partitions due to AWS limits

3. Data Model & Querying

Feature Cassandra DynamoDB
Data Model Wide-column store Key-value and document store
Query Language CQL (SQL-like) NoSQL API (AWS SDK or PartiQL)
Indexes Supports secondary indexes but can be inefficient Global secondary indexes (GSIs) and local secondary indexes (LSIs)
Joins & Aggregations No native support, needs application-level joins Limited aggregation with DynamoDB Streams or AWS Lambda

4. Availability & Durability

Feature Cassandra DynamoDB
High Availability Highly available due to decentralized architecture AWS SLA with high availability
Replication Factor Configurable per keyspace Managed, with on-demand backups
Failure Tolerance No single point of failure, supports multi-region Highly resilient within AWS infrastructure

5. Operations & Maintenance

Feature Cassandra DynamoDB
Management Self-managed, requires tuning (garbage collection, compaction) Fully managed by AWS
Cost Model Infrastructure-based (costs depend on node count, storage, and I/O) Pay-per-use (read/write throughput, storage, requests)
Backups & Restore Supports snapshots and incremental backups Managed automatic backups & point-in-time recovery
Monitoring Requires external monitoring tools (Prometheus, Grafana) Built-in AWS CloudWatch metrics

6. Security & Compliance

Feature Cassandra DynamoDB
Access Control Role-based authentication (internal or LDAP) IAM-based authentication & fine-grained access control
Encryption Supports encryption at rest and in transit Encryption at rest, in transit, and AWS KMS integration
Compliance Needs manual configuration for regulatory compliance HIPAA, PCI DSS, SOC, GDPR, and more by default

7. Use Cases

Feature Cassandra DynamoDB
Best For High-write workloads, multi-datacenter deployments, real-time analytics Serverless applications, low-maintenance use cases, AWS-native workloads
Not Ideal For Complex transactions requiring strong ACID guarantees Large-scale, multi-cloud, or on-premise deployments

8. Summary Table

Feature Cassandra DynamoDB
Ownership Open-source (Apache) AWS-managed
Scalability High, but requires manual tuning Auto-scalable, managed by AWS
Performance High write throughput, tunable consistency Predictable latency, AWS-optimized
Management Requires expertise, self-hosted Fully managed
Cost Fixed infrastructure costs Pay-as-you-go pricing

When to Choose Cassandra?

  • You need multi-cloud or on-premise deployment.
  • You want full control over configuration, replication, and tuning.
  • You are handling high-volume write-heavy workloads (e.g., logging, IoT).

When to Choose DynamoDB?

  • You want a fully managed solution with zero maintenance.
  • You are building AWS-native applications.
  • You prefer pay-per-use pricing and built-in auto-scaling.

Would you like me to dive deeper into a specific area? 🚀

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