Preface:

• Today is the day of buzz words - NoSQL, Big Data, Web-scale, Sharding, Eventual consistency, ACID, CAP theorem, Cloud services, MapReduce, Real-time
• Driving forces for development in data related systems
  • Huge scale needs efficient processing of traffic and data
  • Agility to test things quickly is really the key driver
  • Prallelism is going to increase
  • IaaS has revolitionised the cloud and everyone has ability to excute things no matter which part of the world you are in
• An application is data intensive if data is primary challenge in terms of quantity, complexity & speed of change
• Scalable, available, resilient and curosity
• Building for scale that you don’t need is wasted effort and may lock you into an inflexible design. In effect, it is a form of premature optimization.

Foundations of data systems:

Chapter 1: - Reliability - Software failures & bugs - Scalability - Load, Performance, Latency & Throughput - Maintainability - Operability, simplicity & evolvability - Applications need common functionality like databases, caches, search and filter, stream processing & batch processing