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Optimize Performance and Scalability

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The document discusses strategies for optimizing performance and scalability in data management. It outlines the pros and cons of different approaches such as extract and query versus direct query and suggests various scalability and performance strategies. Examples include in-memory databases and real-time dashboards.

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© Eckerson Group LLC Optimize Performance and Scalability Wayne W. Eckerson
© Eckerson Group LLC Optimize Scalability and Performance Pros: Consistently fast queries Cons: Summary data, stale data Pros: Query all data, fresh data Cons: Query performance Speed Scalability Approach: Extract and Query Approach: Direct Query Scalability strategies - More hardware (RAM, clusters) - Linked databases - Drill to detail Examples: In-memory databases, OLAP on Hadoop Performance Strategies - Native APIs - Caching - Projections Examples: Real-time dashboards; data sharpening

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Optimize Performance and Scalability

  • 1. © Eckerson Group LLC Optimize Performance and Scalability Wayne W. Eckerson
  • 2. © Eckerson Group LLC Optimize Scalability and Performance Pros: Consistently fast queries Cons: Summary data, stale data Pros: Query all data, fresh data Cons: Query performance Speed Scalability Approach: Extract and Query Approach: Direct Query Scalability strategies - More hardware (RAM, clusters) - Linked databases - Drill to detail Examples: In-memory databases, OLAP on Hadoop Performance Strategies - Native APIs - Caching - Projections Examples: Real-time dashboards; data sharpening