skip to main content
Close Icon We use cookies to improve your website experience.  To learn about our use of cookies and how you can manage your cookie settings, please see our Cookie Policy.  By continuing to use the website, you consent to our use of cookies.
Global Search Configuration


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.


  • 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


  • Catalyst
  • Ovum view
  • Key messages


  • 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


  • Methodology
  • Further reading
  • Author

Recommended Articles


Have any questions? Speak to a Specialist

Europe, Middle East & Africa team: +44 7771 980316

Asia-Pacific team: +61 (0)3 960 16700

US team: +1 212-652-5335

Email us at

You can also contact your named/allocated Client Services Executive using their direct dial.
PR enquiries - Email us at

Contact marketing -

Already an Ovum client? Login to the Knowledge Center now