How LinkedIn Uses MongoDB
9 engineering articles about MongoDB from LinkedIn's engineering team
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The article discusses LinkedIn's open sourcing of DataHub, a metadata search and discovery platform, detailing its development journey from WhereHows to DataHub.
ApacheAWSAzureDependency InjectionDockerElasticsearchGoogle CloudJSONKubernetesMicroservicesMongoDBMySQLNeo4jOracleSpring
Kerem Sahin
15 min read
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The article discusses the development and implementation of LinkedIn Skill Assessments, which are standardized tests designed to validate user skills across various domains.
Christian Mathiesen
8 min read
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The article discusses the challenges of managing software dependencies at scale within LinkedIn's engineering environment, which includes over 10,000 separate software codebases.
The article discusses the complex migration of SlideShare's technology stack to LinkedIn's data centers, highlighting the challenges faced and the strategies employed to ensure a seamless transitio...
The Skynet Project is a comprehensive set of tools designed to monitor, scale, and auto-heal cloud systems.
The article discusses the implementation of Hadoop and HBase for near real-time analytics at SlideShare, detailing the upgrade process, technology selection, and the resulting improvements in data ...
The article discusses geographic trends in skills as revealed by LinkedIn's Endorsement feature, highlighting differences in skill sets among technology hubs in the United States.
The article provides ten performance optimization tips for Node. js applications, specifically derived from LinkedIn's mobile server experience.
Shravya Garlapati
6 min read
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This article serves as an introduction to MongoDB, highlighting its growing popularity as a NoSQL database for web applications.
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