Javier Ramírez

When doing real-time analytics, you not only want your database to ingest as quickly as possible, but also to have your data available for (fast) querying as soon as possible.

In this session I will show you the technical decisions we made when building QuestDB, an open source time-series database, and how we can achieve over a million row writes per second without blocking or slowing down the reads.

All the cool cats are using Redis and with reason: It's fast, it's robust, it's easy, and it's web scale. Redis is powering sites like twitter, instagram or pinterest, but you can also benefit from the power of redis even in a more modest project.

In this session I will talk about what is redis, what you can do with it, how you can use it from your application, why you should be using it already and some common patterns when dealing with it. I will talk about:

what REALLY FAST means Redis data structures

How twitter, pinterest or instagram use redis.

queuing slow operations using redis for cross-language development atomic counters and generating sequences dealing with temporary data in your application redis as a cache how to store relational data in a non relational data store interesting problems when distributing your application.

Using Lua scripting for atomic operations