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Apache Spark and Apache Ignite: Where Fast Data Meets the IoT

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It’s not enough to build a mesh of sensors or embedded devices to get more insights about the surrounding environment and optimize your production. Usually, your IoT solution needs to be capable of transferring enormous amounts of data to a storage or cloud where the data has to be processed further. Quite often, the processing of the endless streams of data has to be done almost in real-time so that you can react on the IoT subsystem’s state accordingly, and in time.

During this session, see how to build a Fast Data solution that will receive endless streams from the IoT side and will be capable of processing the streams in real-time using Apache Ignite’s cluster resources. In particular, learn about data streaming to an Apache Ignite cluster from embedded devices and real-time data processing with Apache Spark. Session hashtag: #SFdev25

Denis Magda, Product Manager at GridGain

About Denis

Denis is an expert in distributed systems and platforms who developed his skills by consistently contributing to Apache Ignite In-Memory Data Fabric and helping GridGain In-Memory Data Fabric customers build a distributed and fault-tolerant solution on top of their platform.

Before joining GridGain and becoming a part of Apache Ignite community, Denis worked for Oracle Inc. where he led Java ME Embedded Porting Team helping Java opening new boundaries by entering IoT market.

Currently, Denis takes the role of Product Manager in GridGain and PMC Chair in Apache Ignite, leading both products to an exciting future.