Get started with real-time Data Streaming | What is Data Streaming?

An overview of data streaming, pros and cons as well as discussing some of the methods developers use to implement real-time solutions, and how users can set up their first stream.

In the modern era, everyone expects their data the second it’s updated.

Large corporations and Fortune 500 companies depend on this data to be able to predict consumer tastes or estimate where the forces of supply and demand are moving the market. Real-time data is all part of a modern data strategy.

In turn, many companies are working to modify their batch-style data pipelines into real-time data streams. Real-time data streams provide the ability for analysts, machine learning researchers, and data scientists to develop metrics and models that run as soon as new data is created.

This has become a useful solution for companies that manage manufacturing operations, movie streaming, and detect issues in system logging. Real-time analytics are becoming more popular as well as more feasible for companies of all sizes, as the cloud provides various tools that can be quickly implemented.

In this webinar, we will be outlining some of the various real-time database tools and some of their pros and cons as well as discussing some of the methods developers use to implement real-time solutions. Our goal will be to provide those who attend an understanding of data streaming as well as demonstrate how users can set up their first stream.

Presenter Bio:
Ben is a Seattle-based Data Scientist and Engineer working in San Francisco, California. He has extensive experience designing ETL pipelines, databases, websites, and other software products for startups and pre-established corporations.

Table of Contents:
0:00 – Introduction
0:45 – Data streaming
2:14 – Message cues
5:19 – Message duplication
8:10 – Topics
9:39 – Message guarantee
11:10 – Kafka versus AWS
12:37 – Flink
14:09 – Apache storm
15:12 – Streaming database
16:00 – Materialise
17:31 – Federated queries
19:41 -QnA

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