Effective Design Patterns in NewSQL
summary
Overview of a working NewSQL prototype (VMware SQLFire) that converts a star schema into replicated tables and partitioned by flight ID layouts, runs on three VMs with JDBC clients, and demonstrates dynamic rebalance and zero data loss when adding/removing nodes. Claims: synchronous in-cluster replication, ACID cross-node transactions with optimistic fail‑fast locking, single‑hop key access, and embedded JVM mode. Demo data: ~500 flights, ~542 availability rows; async write‑behind to MySQL uses conflation, queue size 100 and 1s flush.
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chapters (23)
- 0:00Introduction to new SQL
- 2:00Relational database limitations
- 3:30Performance issues and locking
- 4:55Predictability and scalability
- 7:47Next-generation database themes
- 9:48Scaling and developer control
- 11:07High availability and elasticity
- 13:10Challenges of manual sharding
- 15:35SQLFire overview
- 18:52Architecture and deployment
- 23:22Data modeling and partitioning
- 27:52Persistence and partitioning options
- 29:21System components and connection
- 33:20Demonstration: schema and scaling
- 40:29Demonstration: data rebalancing
- 45:33Designing for scale-out
- 57:12Cache patterns and write-behind
- 1:03:14Demonstration: cache listener
- 1:11:13Embedded mode and data procedures
- 1:15:04Asynchronous replication and recap
- 1:17:08Consistency and concurrency models
- 1:21:45Transaction handling and storage
- 1:27:43Final Q&A
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