Databases
DynamoDB at Serverless Scale
DynamoDB rewards careful design. We model tables around your access patterns so reads stay fast and costs stay predictable as traffic grows.
Overview
DynamoDB
Amazon DynamoDB is a fully managed NoSQL key-value and document database on AWS. It offers low-latency reads and writes, on-demand or provisioned capacity, global tables, streams and tight integration with Lambda, API Gateway and other AWS services. There are no servers to patch and no instances to size. Data is replicated across multiple availability zones within a region by default.
The trade-off is that DynamoDB has no ad hoc joins, so the data model must be designed around known access patterns. We start by listing those patterns, then design partition and sort keys, global secondary indexes and, where appropriate, single-table layouts. We pay attention to hot partitions, item size limits and consistency options, and set up TTL, streams and backups. We are candid when a relational database is the simpler answer.
Context
Why teams choose it
- 01
Fully managed operations
No servers, patching or replication to manage; AWS handles scaling and durability.
- 02
Consistent low latency
Key-based access stays fast regardless of table size when the model suits the workload.
- 03
Natural serverless pairing
DynamoDB integrates directly with Lambda, Streams and API Gateway for event-driven designs.
- 04
Pay-per-use capacity
On-demand mode matches spend to traffic, which suits spiky or unpredictable workloads.
Capabilities
What we build with it
- 01
Access-pattern modeling
Key design and single-table or multi-table layouts derived from your real queries.
- 02
Secondary indexes
Global and local secondary indexes chosen to support additional queries without waste.
- 03
Serverless integration
Lambda, API Gateway and EventBridge pipelines triggered by DynamoDB Streams.
- 04
Capacity and cost tuning
Choosing on-demand or provisioned capacity, and avoiding hot partitions and oversized items.
- 05
Data lifecycle
TTL expiry, point-in-time recovery, backups and exports to analytics storage.
- 06
Global tables
Multi-region replication for availability and latency across geographies.
Typical projects
- Serverless backend data stores
- Session, cart and user state
- High-volume event and IoT ingestion
- Leaderboards and counters
- Metadata for object storage
Ecosystem & tooling
- Amazon DynamoDB
- AWS Lambda
- DynamoDB Streams
- API Gateway
- AWS SDK
- PartiQL
- NoSQL Workbench
- AWS CDK
Approach
How we work with it
- 1
Assess
We review your goals and any existing code to decide where this technology fits best.
- 2
Architect
We plan structure, integrations, data flow and hosting before writing production code.
- 3
Build
Features ship in small, reviewed increments with automated checks along the way.
- 4
Release & maintain
We deploy, monitor and keep dependencies and versions up to date.
FAQs
Common questions
Have a question that is not covered here? Get in touch.
Can DynamoDB replace a relational database?
Only when your access patterns are known and key-based. It does not support joins or flexible ad hoc queries, so workloads that need them are often better in PostgreSQL or MySQL.
What is single-table design?
It stores multiple entity types in one table, using key patterns to fetch related items in one request. It can be efficient but is harder to read and change, so we use it where the performance benefit is worth it.
How do costs work?
You pay for reads, writes and storage, either per request in on-demand mode or via provisioned capacity. Poor key design or large items can raise cost, which is why modeling comes first.
Does DynamoDB support transactions?
Yes, it offers transactional reads and writes across items, with limits on size and item count. We use them selectively because they cost more than standard operations.
Let's build what's next
Tell us about your idea, product or legacy system. Send us a message and we will help you scope the right next step.