Spring Data

Preface

Overview of the New Data Access Landscape

The data access landscape over the past seven or so years has changed dramatically. Relational databases, the heart of storing and processing data in the enterprise for over 30 years, are no longer the only game in town. The past seven years have seen the birth—and in some cases the death—of many alternative data stores that are being used in mission-critical enterprise applications. These new data stores have been designed specifically to solve data access problems that relational database can’t handle as effectively.

An example of a problem that pushes traditional relational databases to the breaking point is scale. How do you store hundreds or thousands of terabytes (TB) in a relational database? The answer reminds us of the old joke where the patient says, “Doctor, it hurts when I do this,” and the doctor says, “Then don’t do that!” Jokes aside, what is driving the need to store this much data? In 2001, IDC reported that “the amount of information created and replicated will surpass 1.8 zettabytes and more than double every two years.”^[1] New data types range from media files to logfiles to sensor data (RFID, GPS, telemetry...) to tweets on Twitter and posts on Facebook. While data that is stored in relational databases is still crucial to the enterprise, these new types of data are not being stored in relational databases.

While general consumer demands drive the need to store large amounts of media files, enterprises are finding ...