Analyst Report: DIY Storage vs. Hyper-converged Systems

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The hyperscale infrastructure used by Amazon, Google, Microsoft, and Facebook delivers extreme performance that upends the way service providers and IT managers do business. Using commodity servers, networking, storage, and a DIY approach, enterprise IT managers are able to respond to the demands for mobile and cloud.

Historically, the IT pendulum swings between divergence (using best-of-breed components) and convergence (turnkey completely integrated and engineered systems) every 5 to 10 years. DIY is a swing back to divergence, as are the software-defined data center, elastic infrastructure, bare-metal infrastructure, containers, and object storage.

What makes the current trend unique is that while divergence is gaining momentum, so is convergence with hyper-convergence, engineered systems, appliances, and software-defined compute/networking/ storage that is shrink-wrapped in hardware. Most IT managers see the paths as contradictory, but that is not always the case.

This report explains which approach offers the best short-term and long-term results in operational efficiencies, adaptability, manageability, and the total cost of ownership (TCO).

Key highlights from this report include:

  • Financially unsustainable, storage costs are now the largest single-line item in the IT budget.
  • DIY storage minimizes costs significantly by using off-the-shelf server components.
  • Hyper-convergence improves storage scalability and manageability, but introduces potential vendor lock-in.
  • No one answer is right for every IT organization or every storage project.

Thumbnail image courtesy of camij/iStock.

Table of Contents

  1. Summary
  2. What Needs to Be Fixed
  3. Hardware Selection for Software-Defined Storage
  4. DIY Eliminates Storage Problems and Costs
  5. Hyper-convergence: Simplicity Delivered
  6. Eliminating Storage Problems with Hyper-convergence
  7. DIY vs. Hyper-convergence
  8. Summary and Key Takeaways
  9. About Marc Staimer
  10. About Gigaom Research

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