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 …

Distributed stream processing frameworks have gained widespread adoption in the last
decade because they abstract away the complexity of parallel processing. One of their key …

Serverless computing is currently the fastest-growing cloud services segment. The most
prominent serverless offering is Function-as-a-Service (FaaS), where users write functions …

More and more use cases require fast, accurate, and reliable processing of large volumes of
data. To do this, a distributed stream processing framework is needed which can distribute …

Transactional stream processing (TSP) strives to create a cohesive model that merges the
advantages of both transactional and stream-oriented guarantees. Over the past decade …

Providing strong fault-tolerant guarantees for the modern cloud is difficult, as application
developers must coordinate between independent stateful services and ephemeral compute …

Stream processing is widely used for real-time data processing and decision-making,
leading to tens of thousands of streaming jobs deployed in ByteDance cloud. Since those …

Stream processing in the last decade has seen broad adoption in both commercial and
research settings. One key element for this success is the ability of modern stream …

Single-node multi-core stream processing engines (SPEs) can process hundreds of millions
of tuples per second. Yet making them fault-tolerant with exactly-once semantics while …

Serverless computing is currently the fastest-growing cloud services segment. The most
prominent serverless offering is Function-as-a-Service (FaaS), where users write functions …