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Databricks Job Cluster and SQL Endpoint - discuss Photon

Spark/Big Dataeasy0.5 min readPremium

**Why these matter**: Right compute for workload = cost and performance. **Job clusters**: Ephemeral; spin up for job; scale-to-zero. Cost-effective for batch. **SQL warehouse**: Always-on for BI; serverless option. **Photon**: Vectorized engine; native C++; 2–5x faster for...

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Expert Answer

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Why these matter: Right compute for workload = cost and performance. Job clusters: Ephemeral; spin up for job; scale-to-zero. Cost-effective for batch. SQL warehouse: Always-on for BI; serverless option. Photon: Vectorized engine; native C++; 2–5x faster for SQL/ETL; different DBU rate. Scalability trade-offs: Job clusters = no idle cost; SQL warehouse = low latency. Photon = better perf, compatible with most Spark SQL. Cost implications: Job clusters for batch; SQL for BI; Photon often reduces total cost via faster runs. Best practice: Job clusters for batch; SQL warehouse for BI; enable Photon for compatible workloads.

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