Data Integration
Connect systems with REST APIs, GraphQL, Kafka streams, and ETL/ELT pipelines.
The problem
Your systems don't talk to each other. Data is siloed, APIs are brittle, and manual syncs are error-prone.
Our approach
Mapping: Document all systems, data flows, and integration points.
Design: Choose the right patterns (REST, GraphQL, Kafka, webhooks) based on latency and volume.
Implementation: Build robust APIs and event-driven pipelines with retries, idempotency, and monitoring.
Testing: End-to-end tests, load testing, and failure scenarios.
Outcomes
Reliable API integrations with error handling
Event streaming with Kafka or RabbitMQ
Data validation and schema enforcement
Monitoring and alerting for failures
Sample deliverables
- REST/GraphQL APIs with documentation
- Kafka producers and consumers
- ETL/ELT pipeline code
- Monitoring dashboards (metrics, logs, traces)
- Integration tests and runbooks
Timeline
4–8 weeks for initial integrations; ongoing pipeline development.
Tech stack
FAQs
Can you integrate with legacy systems?
Yes. We've worked with SOAP, XML, and proprietary protocols.
How do you handle failures?
Retries, dead-letter queues, and circuit breakers. We design for resilience.
What about real-time integrations?
We use Kafka, webhooks, and WebSockets for low-latency data flows.
Ready to get started?
Book a thirty minute technical scope call. We will review your requirements and respond with a timeframe and estimate.
Request a scope call