Independent scaling of storage and computing resources for data management has met with early success in cloud environments. Data and analytics leaders thinking of using the cloud must embrace this approach — and the technologies it may enable in future — when devising a long-term cloud strategy.
Impacts and Recommendations
- Separation of storage and computing resources could enable data and analytics leaders to overcome many of the scalability and flexibility problems inherent to distributed cloud architectures
- Together, capable CSPs and an increasing choice of CSP-independent DBMS software will gradually reduce data and analytics leaders' concerns about CSP "lock-in"
- The flexibility of distributed storage approaches, decoupled from application processing, will present data and analytics leaders with opportunities for cloud service arbitrage with a single CSP or multiple CSPs
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