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EVENT DETAILS |
Scalability, performance, & availability have historically been seen as separate tunables. Up to this point, the common perspective has been that a database system could have two but not all three of these characteristics. The advancement of Distributed SQL as a primary data platform has reshaped these assumptions.
Join the Data at Scale meetup where you will connect with industry-leading data experts & practitioners. We will be exploring the various challenges & obstacles that come with scaling data, as well as sharing practical experiences & best practices related to distributed SQL, data warehousing, data engineering, & data for model training (such as the kind that fuels AI models like ChatGPT).
Also enjoy delicious food & drinks, receive some cool swag, & even have the opportunity to win lucky draw prizes.
Agenda (EST):
* 5:00pm~6:00pm: Checkin, Food/drink & networking
* 6:00pm~6:40pm: Tech talk: scaling data platform on hybrid transactional & analytical processing
* 6:40pm~7:30pm: Hands-on workshop & Demo
* 7:30pm: Open discussion & Mixer
Scaling Data Platform on Hybrid Transactional & Analytical Processing
Speaker: Bill Kendall @PingCAP
Abstract: Join us as we explore TiDB & TiDB Cloud, a fully-managed DBaaS offering of TiDB. In this tech talk session, we will discuss:
- Horizontally scalable, distributed architecture
- Challenges of legacy scaling architectures
- Enables fully ACID OLTP plus access to deep aggregation on real-time data
- Simplifies the data ecosystem by eliminating the need for multiple niche platforms & the connecting data pipelines
Hands-on Workshop & Demo
Abstract: Bring your laptop if you are eager to take part in the hands-on workshop. In this workshop session, you will learn:
- Introduction to TiDB managed Cloud platform
- Deploy a serverless TiDB Cluster in the Cloud
- Explore TiDB Cloud console functions & features
- Use SQL Smart Optimizer delivers fast query results
- Leverage AI to generate SQL queries with ChatGPT
Venue:
WeWork, 408 Broadway, New York, NY 10013
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