Automating Query Caching with Data Grids Roland Lee VP of Product - PowerPoint PPT Presentation

Automating Query Caching with Data Grids Roland Lee VP of Product

Agenda Intro to Database Proxy concept • Query caching • Other use cases • Demo • 2

Executive Summary Database Proxies: • • Improves SQL read/write performance and reliability • Deployment requires no application changes 3

Database Proxy Vendors Feature ProxySQL ✓ ✓ ✓ ✓ Automated Failover ✓ ✓ ✓ ✓ Read/Write split ✓ Database Vendor Neutral Automated Cache ✓ invalidation Reduces network latency ✓ 4

IMDG vs. Database Proxies Amazon ElastiCache ProxySQL • May be “good enough” • Best scale & performance • Existing applications, small dev • Greenfield applications • No code changes • Requires code changes 5

Transparent Database Proxy Click to add text

Software Package Options Application Server Application Server Application Application Vendor Database Heimdall Data Driver JDBC driver, .jar JDBC file Vendor JDBC Driver Runs as an Heimdall Data Proxy agent Any JDBC data source 7

Database Proxy Platform APPLICATION QUERY AUTOMATED BATCH CACHING FAILOVER PROCESSING ACTIVE READ/WRITE CONNECTION DIRECTORY SPLITS POOLING HEIMDALL DATABASE PROXY PLATFORM Aurora, RDS, Redshift 8

Heimdall Centralized Deployment Database Proxy Tier Application SQL Application Server Heimdall Heimdall DB Proxy Heimdall DB Proxy DB Proxy Application Heimdall Application Server Central Console 9

Heimdall Distributed Deployment Application Servers Heimdall Application Amazon Aurora Heimdall Data Heimdall Application Server Application RDS, Redshift Data Database Application Server Application Proxy Application Server SQL Analytics Audit Logging Heimdall Application Server Central Console ElastiCache 10

Use Cases

How Caching Works Uses real-time analysis and statistics on: • Query frequency and variability • Relative performance of Cache vs. Database Provides: • Auto-cache only if there is a performance benefit • Cache recommendations and benefits 12

Caching and Read/Write Splits SQL SQL Heimdall Application DB Proxy Write Local Cache App VM 1 L2 Cache Read 1 App VM 2 Local Cache Read 2 SQL SQL Heimdall Application DB Proxy 13

SQL Analytics Very cacheable. 700 µ s per query 14

Demo Click to add text

IMDG vs. Database Proxies Amazon ElastiCache ProxySQL • Good enough • Best scale & performance • Existing applications, small dev • Greenfield applications • No code changes • Requires code changes 16

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