In the run-up to Scylla Summit 2018, we’ll be featuring our speakers and providing sneak peeks at their presentations. This interview in our ongoing series is with two speakers holding a joint session: Scylla and KairosDB in Smart Vehicle Diagnostics. The first part of the talk will feature Brian Hawkins speaking on the time-series database (TSDB) KairosDB, which runs atop Scylla or Cassandra. He’ll then turn the session over to Bin Wang of Faraday Future (FF), who will discuss his company’s use case in automotive real-time data collection. Brian, Bin, thank you for taking the time to speak with me. […]
We recently concluded testing and benchmarking Scylla with KairosDB. The settings and results of this work can be found in the blog post, KairosDB and Scylla: A Time-Series Solution for Performance and Scalability, and in our documentation. In this post, we will share the questions and poll results from our recent live webinar with Brian Hawkins, the creator of KairosDB.
KairosDB, a time-series database, provides a simple and reliable tooling to ingest and retrieve chronologically created data, such as sensors’ information or metrics. Scylla provides a large-scale, highly reliable and available backend to store large quantities of time-series data. Together, KairosDB and Scylla provide a highly available time-series solution with an efficiently tailored front-end framework and a backend database with a fast ingestion rate.
What fascinates me most about databases is how they can be used for storing time series data. This use case is important for Internet of Things (IoT) devices and data analytics. Everyone should at least be able to relate to a time series database use case as many are likely to have devices in their home collecting and sending data such as a smart thermostat or phone or wrist device gathering your fitness activity. Wouldn’t it be nice to know how the infrastructure works behind the scenes and how to create a time series database? In this post, I will […]
Introduction A highly available time-series solution requires an efficient tailored front-end framework and a backend database with a fast ingestion rate. KairosDB provides a simple and reliable way to ingest and retrieve sensors’ information or metrics, while Scylla provides a highly reliable and performant backend database that scales indefinitely, and can store large quantities of time-series data.
This is Part 2 in a series on Thrift support in Scylla. Part 1 is here.