queries per second
avg latency for 2.5+ billion items
- Backend systems were crashing because Oracle couldn’t effectively scale reads
- Memcached had reliability issues and was difficult to manage
- Needed built-in replication and cluster expansion without sacrificing high performance
- Couchbase is used for all in-memory storage in the datacenter, powering 10+ million queries per second
- Tremendous performance at scale, averaging <4ms latency for over 2.5 billion items
- Ease of use, built-in replication and cluster expansion, and automatic partitioning reduced operations costs
Couchbase is a highly scalable, distributed data store that plays a critical role in LinkedIn’s caching systems.
Michael Kehoe Senior Staff Site Reliability Engineer, LinkedIn
- Source-of-truth data stores
Evolution of Couchbase at LinkedIn
Learn how Couchbase’ replication and high performance enabled a number of mission-critical use cases at LinkedIn.
Couchbase Ecosystem at LinkedIn
Understand the topology, data pipelines and key entities in LinkedIn’s Couchbase deployment and how they interact together.
Leveraging SaltStack to Scale Couchbase
See how Couchbase powers one of the highest-performing critical backend services at LinkedIn.
Monitoring Production Deployments: The Tools
Couchbase and LinkedIn present strategies for production system monitoring.
Going All In: From a Single Use Case to Many
LinkedIn talks in depth about leveraging Couchbase to power a wide range of diverse products and services.