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cover of episode #24 DoK Community: The architecture of a distributed database // Jim Walker, Lisa-Marie Namphy & Keith McClellan

#24 DoK Community: The architecture of a distributed database // Jim Walker, Lisa-Marie Namphy & Keith McClellan

2021/1/14
logo of podcast Data on Kubernetes Community

Data on Kubernetes Community

Shownotes Transcript

Abstract of the talk…

Cockroach Labs has built a database architected from the ground up to be distributed. It is a perfect fit for the cloud and Kubernetes as it naturally scales and survives without manual interaction. The unique architecture of CockroachDB delivers some key innovations that may not only provide value for your applications but might also give you insight into the challenges/solutions in distributed systems.

In this session, we will deliver a deep-dive exploration into the internals of the database, exploring the following, and more:

  • How the database uses KV at the storage layer to effectively distribute data

  • How Raft and MVCC are used to guarantee serializable isolation for transactions

  • How Cockroach automates scale and guarantees an always-on resilient database

  • How to tie data to a location to help with performance and data privacy

Bio…

Jim has been a product marketer for almost twenty years and before that he coded professionally in Smalltalk, C++ and Java. He still codes and likes to dive deep into tech so that he can help translate complex topicsinto consumable forms.

Over the course of his career he has focused on emerging tech and has been directly involved in creating six categories. He prides himself as an advocate of the developer and a rabid open source software promoter.

His list of startups that he’s helped build include Servgate, Vontu (acquired), Initiate Sytems (acquired), Talend (IPO), Hortonworks (IPO), EverString (acquired), CoreOS (acquired) and is currently the VP of a Product Marketing at pre-IPO, Cockroach Labs.

Key take-aways from the talk…

We will dive deep into the architecture of the database and explicitly cover the following areas:

  • Ranges (partitions): SQL to KV

  • RAFT

  • Distributed Data: Range Distribution, Scale and Resilience

  • Distributed Transactions

  • Distributed SQL Execution

  • Distributed Latency

  • Distributed Performance Optimizations