DynamoDB Consulting Services
Expert NoSQL data modeling, performance optimization, and scalable architecture design for Amazon DynamoDB. Build high-performance serverless applications with single-digit millisecond latency.
Why Choose Our DynamoDB Consulting?
Comprehensive DynamoDB expertise to build scalable, cost-effective NoSQL solutions
Data Modeling & Access Patterns
Expert single-table design, partition key selection, and access pattern optimization for efficient queries and minimal cost.
- • Single-table vs multi-table design
- • Partition key and sort key strategy
- • Hot partition prevention
Global Tables & Replication
Multi-region replication for global applications with automatic conflict resolution and low-latency local reads.
- • Multi-region active-active setup
- • Conflict resolution strategies
- • Cross-region disaster recovery
DynamoDB Streams
Real-time change data capture for event-driven architectures, materialized views, and cross-service data synchronization.
- • Lambda trigger integration
- • EventBridge Pipes setup
- • Change data capture patterns
DAX Caching
DynamoDB Accelerator implementation for microsecond latency and read-heavy workload optimization with minimal code changes.
- • DAX cluster deployment
- • Cache invalidation strategies
- • TTL and eviction policies
Capacity Planning (On-Demand vs Provisioned)
Cost optimization through capacity mode selection, auto-scaling configuration, and workload analysis for predictable or variable traffic.
- • On-demand vs provisioned analysis
- • Auto-scaling policy setup
- • Reserved capacity planning
GSI & LSI Design
Global and local secondary index design for flexible query patterns without compromising performance or exceeding cost budgets.
- • GSI projection optimization
- • Sparse index patterns
- • Index capacity management
Our DynamoDB Technology Stack
Comprehensive tooling and services for DynamoDB excellence
DynamoDB Core
- • Tables
- • GSI (Global Secondary Index)
- • LSI (Local Secondary Index)
- • DynamoDB Streams
Caching
- • DAX
- • ElastiCache
- • CloudFront
- • API Gateway caching
Infrastructure as Code
- • Terraform
- • CloudFormation
- • AWS CDK
- • Serverless Framework
Integration
- • Lambda
- • API Gateway
- • AppSync
- • EventBridge
Transparent Pricing
Flexible engagement models to fit your project needs
Professional
- Advanced data modeling
- DynamoDB Streams setup
- DAX caching integration
- Capacity optimization
- Priority support
Enterprise
- Global Tables setup
- Multi-region architecture
- Performance optimization
- Dedicated architect
- 24/7 support
Frequently Asked Questions
Common questions about DynamoDB consulting services
When should I use DynamoDB vs RDS?
Choose DynamoDB for: serverless applications with unpredictable traffic, single-digit millisecond latency requirements, key-value or document data models, need for global replication, and event-driven architectures. Choose RDS for: complex queries and joins, relational data models, existing SQL applications, ACID transactions across multiple tables, or when your team has strong SQL expertise.
What is single-table design and when should I use it?
Single-table design stores multiple entity types in one DynamoDB table using generic partition and sort keys, enabling efficient queries and reducing costs. It's ideal for complex applications with multiple access patterns, microservices requiring low latency, and scenarios where you want to minimize cross-table operations. However, it requires careful upfront planning of all access patterns and can be harder to understand for teams new to DynamoDB.
How can I optimize DynamoDB costs?
Cost optimization strategies include: choosing on-demand mode for unpredictable traffic or provisioned mode with auto-scaling for steady workloads, using sparse indexes to reduce GSI costs, implementing TTL for automatic data expiration, optimizing item sizes to reduce storage costs, using projection expressions to fetch only needed attributes, leveraging DAX for read-heavy workloads, and monitoring with CloudWatch to identify hot partitions and inefficient access patterns.
What are DynamoDB limits I should be aware of?
Key limits include: 400 KB maximum item size, 20 GSIs per table, 5 LSIs per table (must be created at table creation), 1 MB query/scan result size, 25 item limit for BatchGetItem, 25 put/delete operations for BatchWriteItem, and partition throughput limits of 3000 RCU and 1000 WCU per partition. Understanding these limits is crucial for proper data modeling and application design.
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