In addition to performance and availability, the scalability of the database is also an issue that users need to consider when choosing the database or when the volume of data keeps growing as the business expands. Take Amazon Aurora, the relational database developed by Amazon Cloud Technology, for example, it has good support in storage expansion, horizontal expansion of read nodes, global database expansion, and vertical expansion of single nodes. Aurora now supports up to four write nodes on a horizontal scale-up of write nodes. Users need to select database middleware when the number of concurrent writes is high. This session will show you how to further extend Amazon Aurora’s write extension capabilities with The Apache ShardingSphere and provide a reference for the audience when choosing database middleware. This presentation will cover:

1. Basic introduction to Amazon Aurora and Apache ShardingSphere
2. Apache ShardingSphere-Proxy supports Amazon Aurora dynamic sharding
3. Apache ShardingSphere-Proxy support for Amazon Aurora read/write separation
4. Apache ShardingSphere-Proxy support for Amazon Aurora table Join
5. Apache ShardingSphere-Proxy supports Amazon Aurora Feiover
6. Combination of Apache ShardingSphere-JDBC with Amazon Aurora

Speakers:

Li-li Ma: Amazon Cloud Technology, Database expert architect, Ma Lili, database expert architect of Amazon Cloud Technology, has been conducting research and product innovation in the field of database for more than ten years: From IBM DB2, to MPP parallel data warehouse Greenplum, to Apache HAWQ for computing and storage decoupling, to Amazon Aurora and ElastiCache databases on the cloud. She has published many academic papers on database (SIGMOD, GCC, SKG, PDCAT) at international conferences and holds many international patents. She is a PMC member of the Apache HAWQ project and an early member of the Greenplum team. She has shared “Apache HAWQ 2.x Latest Technology Decryption” at DTCC 2017, shared the PL/Container implementation of Greenplum in the Greenplum community, And shared Amazon Aurora Serverless and MemoryDB on Amazon Cloud Technology platform.