What is Change Data Capture (CDC) and when is it better than batch?
CDC streams row-level changes from database logs in near real time instead of re-extracting full tables on a schedule. Choose CDC when downstream freshness matters (operational dashboards, sync between systems) or when source tables are too large to re-scan nightly.
Fivetran vs custom connectors — what do you recommend?
Managed connectors (Fivetran, Stitch) for standard SaaS sources where engineering time outweighs licence cost; custom Kafka Connect or Python extractors for high-volume databases, unusual APIs, or cost-sensitive scale. Most clients end up with a deliberate mix.
Can you integrate legacy and on-premise systems?
Yes — Oracle, SQL Server, mainframe extracts, SFTP file feeds, and on-prem Kafka. Our legacy modernization practice routinely bridges on-prem estates to cloud warehouses with CDC and secure tunnels.
How do you prevent integration pipelines from silently breaking?
Schema-change detection, contract tests on every source, dead-letter queues with alerting, reconciliation counts between source and target, and SLA dashboards. Breakage is surfaced in minutes, not discovered in month-end reports.
Do you build event-driven architectures?
Yes — Kafka/Confluent topic design, outbox patterns, CQRS separation, and stream processing with Flink or Spark Structured Streaming. One EdTech client moved from nightly batch to sub-3-minute event-driven freshness.