Over the past two decades, database and distributed systems researchers have made significant advances in the development of protocols and techniques to provide data management solutions that carefully balance three major requirements when dealing with critical data: high availability, fault-tolerance, and data consistency. However, over the past few years the data requirements, in terms of data availability and system scalability, from Internet scale enterprises that provide services and cater to millions of users, has been unprecedented. Cloud computing has emerged as an extremely successful paradigm for deploying Internet and Web-based applications. Scalability, elasticity, pay-per-use pricing, and autonomic control of large-scale operations are the major reasons for the successful widespread adoption of cloud infrastructures. In this tutorial, we will first discuss some of the critical distributed systems protocols that are essential for understanding current large scale data management. We analyze the design choices that allowed modern NoSQL data management systems (key-value stores) to achieve orders of magnitude higher levels of scalability compared to traditional databases. With this understanding, we highlight some design principles that make key-value stores especially suitable in the Cloud. We then analyze the need and the revival of SQL database management systems in large cloud settings. Of particular interest are applications which require data management across multiple datacenters. We will therefore explore the data management design space for geo-replicated data and discuss different approaches for replicating data in multi-datacenter environments.