AWS Aurora

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" summary

Amazon Aurora adds a Postgres 9.6 codebase to a log‑structured storage service that writes only change records, coalesces blocks, and backs segments to S3 with six copies across three AZs. Benchmarks show 2–3x performance and up to 85x faster recovery versus vanilla Postgres, read replicas share the same storage for single‑digit‑millisecond propagation, and failover targets aim for ~3–10s. Case studies report zero schema changes migrating from SQL Server, a claimed 11.5x cost reduction, 50% faster page loads and multi‑fold TPS gains.

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" chapters (26)

1. 0:00PostgreSQL Compatibility for Amazon Aurora
2. 1:45Traditional relational databases are hard to scale
3. 2:04Traditional approaches to scale databases
4. 3:41Reimagining the relational database What if you were inventing the database today?
5. 7:08Scale-out, distributed, log structured storage
6. 8:10Amazon Aurora Storage Engine Overview
7. 9:12Amazon Aurora Storage Engine Fault-tolerance
8. 10:12Amazon Aurora Replicas
9. 10:51Amazon Aurora Continuous Backup
10. 11:22Amazon Aurora Instant Crash Recovery
11. 11:57Faster, more predictable failover with Amazon Aurora
12. 13:28Benchmark System Configurations
13. 15:37Amazon Aurora Loads Data 3x Faster Database initialization is three times faster than PostgreSQL
14. 19:22How Does Amazon Aurora Achieve High Performance?
15. 21:08Write 0 Traffic in an Amazon Aurora
16. 24:21Applications Restart Faster With
17. 26:23First Step: Enhanced Monitoring
18. 27:26Performance Insights at a glance
19. 28:11Beyond Measuring Database Load
20. 28:43Amazon Aurora with PostgreSQL Compatibility - Launch Roadmap
21. 30:04TechnologyOne
22. 31:20The Amazon Aurora Database Family
23. 32:02Uberfusion Case Study - Data Migration for SSO Media
24. 36:17Migration Steps
25. 37:01The Solution and Benefits
26. 37:56Questions

" related talks

• 55mAmazon Aurora: A deep-dive into what's newSailesh Krishnamurthy · Percona Live Open Source Database Conference 2017
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