Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more. Pinot uses Apache Helix for managing cluster resources and Apache Zookeeper to store metadata. Pinot has wide adoption at LinkedIn, ranging from internal...
scale Articles
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- Topics:
- scale,
- Developer Productivity,
- Pinot,
- infrastructure
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With over 630 million members, the LinkedIn platform delivers thousands of features that individually serve and store large amounts of diverse data. Protecting, maintaining, and serving data has always been of paramount importance for enriching the member experience and ensuring service reliability. In this blog post, we’ll address a critical part of data...
- Topics:
- scale,
- infrastructure,
- Developer Productivity
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At LinkedIn, we are entrusted with protecting the privacy and data of our members. Storing members’ choices on how they intend their data to be used is vital to building and maintaining member trust, as well as ensuring compliance with legal and regulatory requirements. It is also essential that we respect members’ preferences for how they wish to interact with...
- Topics:
- infrastructure,
- scale,
- trust engineering
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LinkedIn’s engineering teams are distributed around the globe: from California to Bangalore, our engineers are constantly taking a...
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LinkedIn members entrust us with their personal data and we are committed to working hard every day to maintain that trust within a...
- Topics:
- scale,
- Security,
- trust engineering
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LinkedIn’s infrastructure has grown remarkably over the years, and that has kept the Production Infrastructure Engineering teams on...
- Topics:
- infrastructure,
- scale