I build backends that move data at scale.

$ goldengate replicat --target kafka://daas.events
✔ capture  oracle-19c  lag 0.4s
✔ topic    daas.orders.cdc  partitions 12
stream ─────────────────────────────
  14:02:11  INSERT  orders      → kafka
  14:02:11  UPDATE  inventory   → kafka
  14:02:12  DELETE  sessions    → kafka
throughput 18.4k msg/s · consumer lag 0

resource "oci_golden_gate_deployment" "daas" {
  display_name       = "daas-cdc"
  license_model      = "LICENSE_INCLUDED"
  cpu_core_count     = 4
  is_auto_scaling_enabled = true

  deployment_type = "DATABASE_ORACLE"
}

module "kafka_stream" {
  source     = "./modules/streaming"
  partitions = 12
  retention  = "24h"
}

class Query(graphene.ObjectType):
    orders = SQLAlchemyConnectionField(
        OrderConnection,
        tenant_id=graphene.ID(required=True),
    )

    def resolve_orders(root, info, tenant_id):
        # row-level scoping keeps tenants isolated
        return (
            Order.query
            .filter_by(tenant_id=tenant_id)
            .options(selectinload(Order.items))
        )