MongoDB and Elasticsearch are both NoSQL "databases", or more correctly NoSQL data stores that are often compared and contrasted on a head-to-head basis.
But if comparing that way, one could easily miss out on the opportunity to use both together as individual and independent data stores that serve specific purposes to deliver the best overall solution for your application flow and performance needs.
In this talk, Kimberly will discuss the overall aspects of each technology, best use cases, the strengths and weaknesses of each, scaling, and provide examples for each with details for the underlying technology with architectural information and basic functioning of these two data stores.
Join her as she will offer opinions on the best times to use separately as independent data stores plus the chance to combine the two to get the absolute performance often needed by today's applications and the large amounts of data required.
Kimberly Wilkins is an ObjectRocket's Principal Engineer/Database Denizen having over 16 years working on various database platforms primarily with Oracle databases and associated products (RAC, Enterprise Manager, Exadata, GoldenGate). She has worked at ObjectRocket by Rackspace for the last 2 years supporting the MongoDB NoSQL practice area helping customers large and small with their MongoDB implementations and problems.Before that she worked on databases and apps for an early online auto auction site, re-architected multiple enterprise environments to Linux, deployed RAC (early and later versions), and worked closely with storage systems. One notable fun project was re-engineering the database and storage infrastructure 6 months before launch for SWTOR- Star Wars The Old Republic MMO game. In her sparsely indexed spare time she enjoys wine, food, and embracing a variety of knowledge from all sources - currently involving Hadoop Spark, and its peripherals.