In-Memory MongoDB Accelerator: Re-Imagine Ultimate Performance

If you have a medium to large-scale MongoDB deployment, and have scaling challenges and/or a need for more real-time performance, this session is for you. We will introduce a new offering from GridGain that brings in-memory capabilities to the most popular API for unstructured data storage and query - namely MongoDB. We will discuss how you can achieve elastic scale (think automatic transparent re-sharding) up to thousands of nodes, as well as dramatically better performance: higher throughput and lower latency via concurrent locking and parallel read/write operations. We will discuss various options around choosing databases or collections to keep in memory, synchronous and asynchronous persistence, vertical scale with terabytes of off-heap memory, Visor GUI-based management and monitoring, and much more.

Dmitriy Setrakyan is co-founder and CTO of GridGain Systems. Dmitriy has been designing, architecting and developing software and applications for over 15 years and has expertise in the development of distributed computing systems, middleware platforms, financial trading systems, CRM applications and similar systems. Prior to GridGain, Dmitriy worked at eBay where he was responsible for the architecture of performance sensitive high-traffic components of an add-serving system processing several billion hits a day. Before that Dmitriy served as a Lead Architect at Fitech Labs, focusing on high-performance software for trading systems, where he jump-started a new distributed caching and grid computing product line scaling out to 100s computers. Dmitriy holds a Bachelor of Science in Computer Science from University of California at Davis specializing in Networking and Algorithms. Read Dmitriy’s personal blog on Blogger.com.