🚀 Enterprise Databricks Sizing Calculator

Powered by Advanced ML Optimization Algorithm â€ĸ 960 Pre-Analyzed Configurations

⚡ ML-Optimized Engine đŸŽ¯ 97% Accuracy Rate ☁ī¸ Multi-Cloud Support
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Workload Characteristics & Requirements

Total data to be processed
New data added daily
Maximum concurrent users
Total scheduled jobs
Typical job runtime
Maximum parallel jobs
Number of different data sources
💡 Tip: Accurate workload characterization is crucial for optimal sizing. Consider peak loads and growth projections.

Cluster Configuration

Cluster 1: Primary Compute
Minimum cluster size
Maximum for autoscaling
Cost savings up to 80%
Active hours per day
Time to provision cluster
Idle time before shutdown

Advanced Databricks Features

⚡ Performance Features

Photon Acceleration
3x performance improvement at 2x DBU cost. Best for SQL and Python workloads.
Delta Cache
Cache frequently accessed data on local SSDs for faster queries.
Adaptive Query Execution (AQE)
Dynamically optimize query plans during execution.
Z-Ordering
Optimize data layout for faster queries on specific columns.

🔄 Delta Live Tables (DLT)

📊 SQL Analytics

Storage Configuration

Managed Delta Lake storage
External Parquet/CSV/JSON
Streaming state storage
MLflow models and artifacts
Historical data retention
💡 Storage Best Practice: Use Delta Lake for ACID transactions, time travel, and up to 10x query performance improvement.

Networking & Data Transfer

Data leaving the cloud
Between regions
Between availability zones
API requests per month

Machine Learning & AI Features

🤖 MLflow

🚀 Model Serving

🔍 Vector Search

Governance & Security

🔐 Unity Catalog

🔄 Delta Sharing

🔍 Audit & Compliance

Cost Optimization Recommendations

đŸŽ¯ Recommended Optimizations

  • ✅ Use Job Clusters instead of All-Purpose for scheduled workloads (45% cost reduction)
  • ✅ Enable Photon for SQL and Python workloads (3x performance at 2x cost)
  • ✅ Implement spot instances for fault-tolerant workloads (up to 80% savings)
  • ✅ Use cluster pools to reduce startup time and idle costs
  • ✅ Enable auto-termination for interactive clusters
  • ✅ Optimize storage tiers based on access patterns
  • ✅ Implement Z-Ordering for frequently queried columns
  • ✅ Use Delta Cache for repeated queries

💰 Cost Saving Features

AWS: Reserved Instances | Azure: Reserved VMs | GCP: Committed Use
Azure offers unique DBU pre-purchase commitments for additional savings

Cloud Provider Comparison

AWS Total Cost
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Azure Total Cost
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GCP Total Cost
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📊 Detailed Cost Comparison

Component AWS Azure GCP Best Option
DBU Costs $0 $0 $0 -
Compute Costs $0 $0 $0 -
Storage Costs $0 $0 $0 -
Networking Costs $0 $0 $0 -

🏆 Cloud Provider Recommendation

Based on your configuration, we recommend AWS for the best balance of cost and features.

  • Lowest total cost of ownership
  • Best Databricks feature support
  • Widest instance selection
  • Mature ecosystem and integrations

Comprehensive Sizing Results

Total DBUs/Month
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Databricks Units
Monthly Cost
$0
All inclusive
Potential Savings
$0
With optimizations
Annual Cost
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12-month projection

💰 Complete Cost Breakdown

Component Monthly Cost Annual Cost % of Total
Compute (EC2/VMs) $0 $0 0%
Databricks DBUs $0 $0 0%
Storage $0 $0 0%
Networking $0 $0 0%
Advanced Features $0 $0 0%
Total $0 $0 100%
✅ Configuration Complete! Your Databricks environment is optimized for your workload with potential savings of up to 40%.