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How Route enables always-on data for over 1 billion+ orders with CockroachDB | RoachFest 24

2024-07-31

RoachFest 2024: Menlo Park | CockroachDB

Description

Route is the leading post-purchase customer experience solution, protecting brands and their customers with shipping insurance, package tracking, fast issue resolution, carbon neutral shipping, and remarketing. Almost since Route’s inception, the company has leveraged CockroachDB to manage its mission-critical order and shipment data. In this talk, Bryan Call, Route’s Senior Principal Engineer, discusses the company’s long journey with CockroachDB and share learnings on running and scaling self hosted CockroachDB on AWS to meet peak demand while avoiding lost revenue from downtime. Testimonial: https://youtu.be/6_avpmFPY6A Case study: https://cockroa.ch/3X3KaZ0 How Route enables always-on data for over 1 billion+ orders with CockroachDB | RoachFest 24 00:00 Introduction 00:17 CockroachDB vs Traditional SQL DB: What happens during a storage failure? 00:42 How typical SQL DBs handle storage failure 02:03 How CockroachDB handles a storage failure 03:25 Who is Bryan Call? 04:30 What does Route do? 05:09 How does CockroachDB help deliver on Route's mission? 06:32 Scalability in CockroachDB 07:49 Route's journey with CockroachDB: A Marathon 08:55 Scaling without data migrations or downtime 09:30 How a resilient database can increase revenue 12:10 CockroachDB architecture at Route 13:17 Running CockroachDB self-hosted in AWS using ECS 16:17 CockroachDB tips and tricks 18:03 How database resilience leads to customer satisfaction 19:28 CockroachDB vs DynamoDB 20:08 CockroachDB vs Traditional SQL 20:29 Why should you choose CockroachDB? 20:55 Query best practices 22:43 When to use covering indexes 23:44 Pros and cons of covering indexes 24:54 Challenges with CockroachDB 26:34 The biggest benefits About CockroachDB: Run mission-critical apps on CockroachDB — the cloud native, distributed SQL database designed for high availability, effortless scale, and control over data placement.