Apache Cassandra has proven to be one of the best solutions for storing and retrieving data at high velocity and high volume.
In the first part of the talk we will discuss how the storage model of Cassandra is ideal for time series use cases, which are often of high velocity and high volume. Time series data is everywhere today: Internet of Things, sensor data, transactional data, social media streams. We go over examples of how to best build data models.
We will also cover pairing Apache Spark with Apache Cassandra to create a real time data analytics platform.
The second part of the talk will present Titan:db, an open source distributed graph database build on top of Cassandra that can power real-time applications with thousands of concurrent users over graphs with billions of edges. It exposes a property graph data model directly atop Cassandra which makes storing and querying relationship data fast, easy, and scalable to huge graphs. This talk demonstrates how Titan's features enable complex, multi-relational databases in Cassandra and discusses how Titan:db has been used in a customer case to store social network data.