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Session Abstract:

Because performance matters when dealing with streaming data – in-memory processing and in-memory data is key. Keeping data in motion is important for the application performance. Organizations building real-time stream processing systems need to use an in- memory paradigm and be able to use any message broker and trust the platform to deliver each message exactly once.

Today’s innovative businesses process ultra-fast data streams at their core – processing must be fault tolerant and continuously adapt to changing data flows. The ability to work with exactly once streams simplifies development and is even more important as real-time streaming spreads.


Kevin Goldstein
Principal Architect at NEEVE RESEARCH

A Principle Architect and low latency developer with over 17 years of experience in building high-performance enterprise applications and trading systems. Kevin specializes in the low latency, messaging and algorithmic arena of trading, and has experience with front, middle and back office systems.

Session Tags

Enterprise, Small / Medium Enterprise,

JAVA, low Latency, in-Memory, microservices, micro-services, PAAS, fintech, HPC, Kafka, IMDG, HTAP, Translitical, IMC, BigData, StreamProcessing, #iiot, streaming, apache, cloud, digitaltransformation, artificialintelligence, ai, ML, machinelearning,

CxO, VP / Director, Middle Management, Technical,


Retail, Banking, Financial Services, Insurance, Healthcare, Government / Public Sector, Pharmaceutical / BioTech

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