RSVP here. Spots limited!
Building Location-Aware Applications with Redis looks at how the geospatial indexing features of Open-Source Redis can be used to support geographical data queries in an application. Using an example bike sharing application, the talk covers how to parse publicly available data feeds provided by bike share systems around the world (such as Hubway in Boston or the CitiBike system in New York City) and index that data in Redis. From there, we look at how to build a query API to find nearby bikes using location information, and how to update the availability data in real-time based on rentals in the system. All of the example code provided will be in Python, but it is very accessible to developers unfamiliar with the language.
As described on it's website (https://redis.io/), "Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker." Its support of useful datatypes and highly optimized access methods make it popular for more than one layer of the stack. Redis has consistently been ranked as the top key-value datastore by DB Engines ( https://db-engines.com/en/ranking/key-value+store ) and has been available in AWS ElastiCache since 2013. It is a worthwhile NoSQL option to consider for your toolbelt.
This talk will discuss leveraging datatypes and APIs for handling points, sets, set searches and intersections for geographic, time-series and live real-time data at speed.
A light dinner will be provided.