Data growth is exponential and organizations are producing it in a myriad of formats. Instead of storing and processing the data at some regular cadence, many in the industry are realizing the benefits of real-time data analytics via stream processing. The move to streaming architectures from batch processing is a revolution in how companies use data. But what is the state of storage for real-time applications, and what gaps remain in the technology we have? How will this technology impact the architectures and applications of the future? Sijie Guo will describe Apache DistributedLog - a high throughput and low latency replicated stream store, discuss what are the challenges on building a stream store for real-time applications, and explore the future of Apache DistributedLog and the big data ecosystem.
