Memory-optimized indexes: how they work – Couchbase Connect 2016

Memory-optimized indexes add fast and scalable secondary indexing capability in Couchbase 4.5. The performance of Global Secondary Indexes can now be accelerated by providing more DRAM and CPU cores. To achieve high-performance in-memory indexing, we designed a new storage engine called Nitro from the ground up, taking advantage of many CPU cores and large DRAM capacity available in modern commodity servers. Couchbase Multi-Dimensional Scaling (MDS) also plays a key role in achieving high scalability for secondary indexing. In this presentation, we cover the key architectural innovations and design of the Nitro storage engine used in memory-optimized indexes. We showcase the performance of memory-optimized indexes in terms of indexing latency, throughput, and scalability compared to regular indexes.

Speaker: Sarath Lakshman, Senior Software Engineer, Couchbase

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