In Memory Data Grids and NoSQL for rapid transactions and Analytics

In Memory Data Grids and NoSQL for rapid transactions and Analytics

Main Speaker:

Tracks:

Data

Seminar Categories:

Data
NoSQL

Course ID:

43684

Date:

24.6.2019

Time:

Daily seminar
9:00-16:30

43684

Overview

In Memory grids provides the following capabilities: Memory distributed on multiple machines, all may be active in each site, nodes added dynamically, all data kept in RAM, data model is Object-based and the data fabric is resilient. In Memory is an important capability for handling Big-Data travels between applications and storage. As data consumption rises – the need for In-Memory efficiency become more clear and obvious.  This seminar explores In-Memory Grid architecture and solutions

NoSQL, and Graph DBs in particular, are also mostly relevant solution for BigData management and streaming. NoSQL allows working with HDFS and handle large amounts of data in intensive concurrent environments.

This seminar explores the challenges and needs, as well as solutions and popular tools for implementing In-memory data management, streaming and querying

Who Should Attend

  • Data scientists
  • Developers in BigData environments

Prerequisites

  • Knowledge of BigData main concepts and the 4V’s
  • Familiarity with any kind of DB

Course Contents

  • In-memory
    • Introduction & the need
    • Challenges
    • Leading tools
      • Redis
      • Spark
    • Data streaming
      • Introduction to asynchronous communication
      • Kafka
    • NoSQL
      • Relevance
      • Types and use-cases
      • Graph DBs
        • Introduction
        • Neo4J


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