Skip to main content
PySparkSnowflakeDatabricks

Photon Execution Engine — When & Why to Use It

✨ Story Time — “Why Did This Query Suddenly Get Faster?”​

Karan, a senior data engineer, receives a message from his analyst:

“Hey… did you change something?
Our dashboard queries are suddenly 2x faster!”

Karan smiles.
He recently enabled Photon, Databricks’ next-generation execution engine.

Photon didn’t just speed up queries…
It reduced compute cost, improved concurrency, and made the whole SQL Warehouse feel snappier.

Let’s break down why.

🧩 What Is the Photon Engine?​

Photon is Databricks’ vectorized, massively parallel execution engine written in C++, built specifically to accelerate:

  • SQL workloads
  • Delta Lake operations
  • BI dashboards
  • Analytics at scale

Photon replaces parts of Spark’s execution pipeline with a highly optimized, CPU-efficient engine.

Designed For:​

✔ Fast scans
✔ Heavy aggregations
✔ Joins
✔ Filtering
✔ Group-bys
✔ Columnar processing

Photon = Spark’s brain on steroids.

🔬 Why Is Photon Faster?​

Photon is fast because it uses:

⚡ 1. Vectorized execution​

Processes data in batches, not row-by-row.

⚡ 2. CPU-level optimizations​

Uses SIMD instructions (Single Instruction, Multiple Data) — like processing multiple values with a single CPU instruction.

⚡ 3. C++ instead of Java​

Fewer overheads, tighter memory management, fewer garbage collections.

⚡ 4. Better I/O handling​

Optimized for Delta Lake and Parquet.

⚡ 5. Smart cache awareness​

Photon aligns with memory/cache boundaries to reduce CPU cycles.

Result: Up to 3x faster than traditional Spark for SQL queries.

🔍 How to Enable Photon​

For SQL Warehouses:​

In Databricks SQL UI →
SQL Warehouse → Settings → Enable Photon

For Clusters:​

"runtime_engine": "PHOTON"

Or in UI:

✔ Enable Photon ✔ Works with DBR 9.1+ and above

Photon works automatically once enabled—no code changes needed.

🎯 When Should You Use Photon?​

🟩 Best Scenarios​

✔ BI Dashboards Faster aggregations → faster dashboards (Power BI, Tableau, Looker)

✔ Large analytic queries Joins, group-bys, window functions, filters

✔ Delta Lake tables Photon accelerates Delta-specific operations like MERGE, UPDATE, DELETE.

✔ Heavy SQL workloads If your team uses mostly SQL → Photon is a must.

✔ Ad-hoc exploration Data scientists benefit from faster interactive queries.

❌ When Photon May Not Help​

Photon is amazing, but not perfect.

Avoid relying on Photon for:

✖ Python UDF-heavy workloads Photon focuses on SQL path, not Python execution.

✖ R or Scala-heavy transformations Photon accelerates SQL, not arbitrary Spark code.

✖ GPU-based ML workloads Photon is a CPU engine, not GPU-focused.

✖ Tiny datasets For small tables, gains are minimal.

🧪 Real-World Example — Photon in Action​

Karan’s team runs a query:

SELECT product_id, SUM(quantity)
FROM transactions
WHERE event_date >= '2025-01-01'
GROUP BY product_id;

Before Photon: 18 seconds

After enabling Photon: 6 seconds

Compute cost: ↓ 40% Dashboard refresh time: ↓ 60% Cluster load: ↓ 35%

Their BI team finally said: “This is the fastest it has ever been.”

⚡ Benefits of Using Photon​

BenefitDescription
Speed3× faster SQL execution
Cost SavingsFewer cluster hours needed
Better ConcurrencyMore users can query simultaneously
Efficient CPU usageOptimized vectorized processing
Delta OptimizedBuilt for Parquet & Delta Lake

🧠 Best Practices​

🟩 1. Always use Photon for SQL Warehouses​

This is where it shines the most.

🟩 2. Convert Python UDFs → SQL Functions​

Let Photon handle them.

🟩 3. Combine Photon + Z-ORDER + OPTIMIZE​

A deadly combination for performance.

🟩 4. Use smaller, faster clusters​

Photon lets you scale down compute.

🟩 5. Benchmark queries before and after​

Most workloads see 2×–5× improvement.

📘 Summary​

  • Photon is Databricks’ C++-based execution engine designed for high-speed SQL and Delta processing.
  • It improves performance, reduces cost, and boosts concurrency.
  • Perfect for BI dashboards, analytics, and heavy SQL workloads.
  • Not ideal for UDF-heavy or non-SQL Spark jobs.
  • Turning on Photon requires no code changes — just enable it and enjoy instant speed.

Photon = Faster queries, lower cost, happier teams.

👉 Next Topic

Cluster Sizing — Choosing the Right Instance Type