AWS data pipelines for teams already on AWS.

Athena is ideal for intermittent querying over S3, with no cluster to manage and pay-per-query cost. Redshift Serverless suits consistent BI workloads that want warehouse semantics without capacity planning. Snowflake runs on AWS and is worth the extra vendor when you need its multi-tenant access controls or cross-cloud portability. We size all three against your real query patterns.

Batch is enough far more often than teams assume, and it is dramatically cheaper to run and debug. Streaming is justified when a decision genuinely depends on sub-minute freshness, such as real-time bidding signals or fraud checks. Hourly batch satisfies most marketing reporting, since the upstream platforms do not update faster than that anyway.

Because hand-built AWS environments cannot be reliably recreated, reviewed or rolled back. With Terraform or CDK, staging matches production, changes go through review, and recovery is a re-apply rather than a reconstruction from memory.

Yes, and that is the normal case. We start by documenting what runs today and what depends on it, then improve incrementally. Wholesale replacement is rarely warranted and always riskier than it looks.