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Market Radar

GigaOm Radar for Cloud Database Platforms v1.0

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Table of Contents

  1. Summary
  2. About the GigaOm Radar Report
  3. Market Categories and Deployment Types
  4. Key Criteria Comparison
  5. GigaOm Radar
  6. Vendor Insights
  7. Analyst’s Take
  8. About Andrew Brust
  9. About Yiannis Antoniou

Summary

Relational databases have been the enterprise’s go-to technology for storing transactional and analytical data for more than four decades. But as with everything else in the technology industry, the cloud has upended the traditional offerings and spurred the creation of a slew of new cloud-native databases. These new platforms have taken advantage of the cloud’s inherent advantages in elasticity, cost of ownership, ease of use, operational simplicity, provisioning flexibility, and more. This has led to the creation of a new paradigm in the database industry, and this shift is actively being enacted in the market.

The new breed of Database as a Service (DBaaS) cloud platforms offer many advantages over traditional counterparts, but it would still be imprudent to break completely from the on-premises past and present. Diligent organizations will survey the market and take a holistic approach that deals with their data needs in totality.

This GigaOm Radar report details the key cloud database platforms in the market and identifies vendors and products that excel. This report will give you an overview of key cloud database platforms, helping you evaluate your existing investments and informing your new ones. Key findings include:

  • Several new cloud-native platforms have been developed, both by traditional on-premises vendors as well as new entrants.
  • Many organizations are already using the platforms extensively and usage is accelerating.
  • Building on cloud-native architectures enables significant flexibility in deployment of the platforms across public and private clouds as well as on-premises.
  • The platforms enable key scenarios around elasticity, performance, data distribution, automation, and data replication that are very difficult to get right in an on-premises environment. This is due to the underlying cloud architecture and is expected to lead to even more capabilities down the line.
  • SQL continues to be the dominant querying language in most cases; however, extensive support for both multi-model databases and the NoSQL model is widely observed.
  • We have grouped the platforms in this report into two distinct categories: relational model database platforms and NoSQL database platforms

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