Every year, developers learn new frameworks and languages not only to enhance productivity, but also to stay relevant in an ever-changing industry. And yet there’s always a chance that tools you learn today won’t be around next year. So you end up wasting your time, and worse, you waste the opportunity to learn something more relevant.
This report examines the benefits of developing on a multi-model database that supports document, graph, relational, key-value, and other data models. Author Eric Laquer of MarkLogic describes tools and techniques for working directly with data as it arrives from the source, enabling your team to explore, on the fly, what a potential solution for a customer will look like.
By leveraging what you already know about modeling and indexing data, a multi-model database will help you apply data management to the DevOps model and move past the limitations of rows and tables altogether.
This report explores:
- How multi-model database management systems support a data-driven approach to software development
- Why applications that support data integration and analytic use cases can break a relational data model
- Case studies of two Fortune 50 companies that successfully adopted multi-model databases
- Why a data-driven approach requires collaboration among DBAs, sysadmins, analysts, and compliance and risk managers
Table of contents
- 1. Introduction
- 2. Data Is Knowledge
- 3. What Software Developers Want
- 4. What DBAs Want
- 5. What the SysAdmin Wants
- 6. Compliance—Risk Management Perspective
- 7. What the Analyst Wants
- 8. Focus on the Data
- Title: Defining Data-Driven Software Development
- Release date: September 2017
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491979273
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