Big Data Systems (BDSs) are an emerging class of scalable software technologies whereby
massive amounts of heterogeneous data are gathered from multiple sources, managed …

Event processing (EP) is a data processing technology that conducts online processing of
event information. In this survey, we summarize the latest cutting-edge work done on EP …

Distributed stream processing systems need to support stateful processing, recover quickly
from failures to resume such processing, and reprocess an entire data stream quickly. We …

A new class of database management systems (DBMSs) called NewSQL tout their ability to
scale modern on-line transaction processing (OLTP) workloads in a way that is not possible …

Realtime data processing powers many use cases at Facebook, including realtime reporting
of the aggregated, anonymized voice of Facebook users, analytics for mobile applications …

An increasingly important system requirement for distributed stream processing applications
is to provide strong correctness guarantees under unexpected failures and out-of-order data …

Stream processing has been an active research field for more than 20 years, but it is now
witnessing its prime time due to recent successful efforts by the research community and …

In this paper, we argue that in many “Big Data” applications, getting data into the system
correctly and at scale via traditional ETL (Extract, Transform, and Load) processes is a …

Stream processing has been an active research field for more than 20 years, but it is now
witnessing its prime time due to recent successful efforts by the research community and …

The concept of state and its applications vary widely across big data processing systems.
This is evident in both the research literature and existing systems, such as Apache Flink …