Amazon Aurora: A deep-dive into what's new
summary
Amazon Aurora separates storage into a scaleout service that writes only redo log records to six copies and commits after a 4-out-of-6 quorum, reducing network IO to ~0.9 IOs/transaction and sustaining ~35x more throughput in a benchmark. Claims include up to 100k writes/sec and 625k reads/sec on r3.8x, replica lag under 20 ms, ~10s crash recovery, zero‑downtime patching, fast DDL, Select INTO S3 and Lambda invocation from stored procedures.
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chapters (36)
- 0:00Intro
- 0:19Agenda
- 0:43Amazon Aurora
- 1:31Re-imagining the relational database
- 2:25Scale-out, distributed, multi-tenant architecture
- 4:47Leveraging cloud ecosystem
- 7:56Automate administrative tasks
- 9:01Aurora customer adoption
- 9:24Who is moving to Aurora and why?
- 11:48Recent announcements
- 12:42MySQL compatibility
- 13:54Aurora Performance Tenets
- 20:2610 traffic in Aurora (Database Node)
- 24:1910 traffic in Aurora (Storage Node)
- 27:1110 traffic in Aurora Replicas
- 31:48Real-life data - read replica latency
- 32:56Asynchronous group commits
- 35:02Adaptive thread pool
- 35:33Aurora lock management
- 36:19Scaling with instance sizes
- 38:07Faster index build (Aug 2016)
- 38:31Hot row contention (Nov 2016)
- 39:25Insert performance (Dec 2015)
- 40:48Non-cached read performance (Dec 2016)
- 41:19High Performance Auditing (Jan 2017)
- 41:57Fast DDL: Aurora vs. MySQL (Mar 2017)
- 42:41Fast DDL Roadmap
- 43:166-way replicated storage
- 44:05Storage Durability
- 44:44Continuous Backup and Point-in-Time Restore
- 45:27Survivable Caches
- 45:53Faster Fail-Over
- 46:31Zero downtime patching (Dec 2016)
- 47:22Zero downtime patching - current constraints
- 48:12What is database backtrack ? Planned for June 2017
- 49:05Near-term Roadmap (3-6 month plan)
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