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Introduction

The headline for big data analytics, data management, and artificial intelligence in 2019 is productivity. The initial steps to harness machine learning to make databases self-driving have been taken. Meanwhile, data engineers and developers are addressing opportunities created by the shortage of data scientists.

Highlights

  • Machine learning is automating database operations.
  • Cloud databases still evolving. The cloud brings distributed transaction processing mainstream. The stars are aligning for graph databases.
  • Developers and data engineers grow more machine learning-savvy.

Features and Benefits

  • Provides recommendations to enterprises on what to look for in evaluating cloud-native databases, and in mobilizing to address requirements to incorporate AI into their applications and insights.
  • Outlines for vendors the opportunities to be served in a market where cloud-native databases and the need for more accessible paths to AI are driving demand.

Key questions answered

  • How will the cloud disrupt the database market in 2019?
  • How are data engineers and software engineers mobilizing to fill opportunities created by the shortage of data scientists?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Recommendations

  • Recommendations for enterprises
  • Recommendations for vendors

Machine learning is automating database operations

  • Oracle opened the door; others are starting to follow
  • How far will self-driving databases go?

Cloud databases are still evolving

  • Beneath the standard checklist, cloud databases continue diverging
  • The standard checklist
  • Behind the façade, lots of differentiation
  • The cloud is reinventing databases
  • How third-party database vendors will play it

The cloud takes distributed transaction processing mainstream

  • Not a new idea
  • The cloud provides the natural home for distributed transaction processing

The stars are aligning for graph databases

  • Solving a familiar problem
  • The skills challenge
  • Standards start expanding the playing field

Data engineers and developers growing more machine learning-savvy

  • Demand for AI professionals keeps rising
  • Machine learning engineer is becoming the go-to profession
  • Python is becoming the top language for ML

Appendix

  • Methodology
  • Further reading
  • Author

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