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.
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.
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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