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Key Criteria/Market Landscape

Key Criteria for Evaluating Cloud Database Platforms v1.0

An Evaluation Guide for Technology Decision Makers

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Table of Contents

  1. Summary
  2. About the Key Criteria Report
  3. Cloud Databases Primer
  4. Report Methodology
  5. Decision Criteria Analysis
  6. Evaluation Metrics
  7. Analyst’s Take
  8. About Andrew Brust
  9. About Yiannis Antoniou

Summary

For more than four decades, if an enterprise wanted to store transactional or analytical data, it would turn to a relational database. However, today the cloud has allowed the creation of a new solution: the cloud-native database.

In this report, we explore these new platforms, which take advantage of the cloud’s inherent qualities—boosting elasticity, reducing cost of ownership, increasing ease of use, creating greater operational simplicity, improving flexibility, and more.

This new class of Database-as-a-Service (DBaaS) cloud platforms demonstrates multiple advantages over more traditional platforms, but most organizations would be unwise to break completely from the old techniques of on-premises and hybrid cloud. Successful organizations will take into account solutions in the market, the capabilities and needs of their internal teams, and their own strategic plans before making decisions on which platforms to adopt.

This GigaOm Key Criteria Report identifies key criteria and evaluation metrics for selecting a cloud database platform. It outlines how to identify the basic requirements of a system, what features serve to differentiate solutions within the market, and what new features now being developed and deployed that we predict will become relevant within the market. It also explores the top-line characteristics—known as evaluation metrics—that ultimately drive decision making.

Key Findings

This report produces a number of key findings. These include:

  • Cloud database platforms are a relatively new development in the long story of database systems. They are, however, based solidly on the established theoretical work done over the past forty years in the areas of relational, object, document, and graph databases. These mature principles are supplemented by the distributed data, replication, elasticity, scaling, and operational characteristics that the cloud enables. Taken together, these concepts represent an important advancement in database systems principles.
  • Building on cloud-native architectures enables significant flexibility in deployment of the platforms, across public and private clouds as well as on-premises.
  • SQL continues to be the dominant querying language in most cases; however, extensive support for multi-model databases and the NoSQL model is widely observed.

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