Getting data out of your traditional database stores into a other database type can be problematic, especially if you want to do it in real-time. Using Tungsten Replicator it's possible to move data from your existing Oracle and MySQL stores into a variety of targets, including Elasticsearch, Kafka and Hadoop. In this session we'll look at the mechanics of each process and how to combine the core replication technology with filters and deployment models to enable complex data movement and concentration.
Optimizing MySQL performance and troubleshooting MySQL problems are two of the most critical and challenging tasks for MySQL DBA´s. The databases powering your applications need to be able to handle heavy traffic loads while remaining responsive and stable so that you can deliver an excellent user experience. Further, DBA´s are also expected to find cost-efficient means of solving these issues. In this presentation, we will discuss how you can optimize and troubleshoot MySQL performance and demonstrate how Percona Monitoring and Management (PMM) enables you to solve these challenges using free and open source software. We will look at specific, common MySQL problems and review the essential components in PMM that allow you to diagnose and resolve them.
When storing time-series data, many developers start with some well-trusted system like Postgres, but as their data hits a certain scale, give up its query power and ecosystem by migrating to a NoSQL or other "modern" time-series architecture.
In this talk, I describe why this trade-off is unnecessary, and how we've built TimescaleDB, an efficient, scalable time-series database engineered up from Postgres. The nature of time-series workloads--appending data about recent events--presents different demands than transactional (OLTP) workloads. We've architected our time-series database to take advantage of and embrace these differences.
TimescaleDB improves insert rates by 15X over Postgres, even on a single node. By right-sizing chunks, it avoids the "performance cliff" Postgres experiences once reaching table sizes of 50+ million of rows, while offering compelling complex query performance improvements. TimescaleDB is packaged as a Postgres extension, released under the Apache