Designing data-intensive applications : the big ideas behind reliable, scalable, and maintainable systems

Incluye índice y bibliografía.

PART I Foundations of Data Systems -- Chapter 1 Reliable, Scalable, and Maintainable Applications -- Thinking About Data Systems -- Reliability -- Scalability -- Maintainability -- Summary -- Chapter 2 Data Models and Query Languages -- Relational Model Versus Document Model -- Query Languages for Data -- Graph-Like Data Models -- Summary -- Chapter 3 Storage and Retrieval -- Data Structures That Power Your Database -- Transaction Processing or Analytics? -- Column-Oriented Storage -- Summary -- Chapter 4 Encoding and Evolution -- Formats for Encoding Data -- Modes of Dataflow -- Summary -- PART II Distributed Data -- Chapter 5 Replication -- Leaders and Followers -- Problems with Replication Lag -- Multi-Leader Replication -- Leaderless Replication -- Summary -- Chapter 6 Partitioning -- Partitioning and Replication -- Partitioning of Key-Value Data -- Partitioning and Secondary Indexes -- Rebalancing Partitions -- Request Routing -- Summary -- Chapter 7 Transactions -- The Slippery Concept of a Transaction -- Weak Isolation Levels -- Serializability -- Summary -- Chapter 8 The Trouble with Distributed Systems -- Faults and Partial Failures -- Unreliable Networks -- Unreliable Clocks -- Knowledge, Truth, and Lies -- Summary -- Chapter 9 Consistency and Consensus -- Consistency Guarantees -- Linearizability -- Ordering Guarantees -- Distributed Transactions and Consensus -- Summary -- PART III Derived Data -- Chapter 10 Batch Processing -- Batch Processing with Unix Tools -- MapReduce and Distributed Filesystems -- Beyond MapReduce -- Summary -- Chapter 11 Stream Processing -- Transmitting Event Streams -- Databases and Streams -- Processing Streams -- Summary -- Chapter 12 The Future of Data Systems -- Data Integration -- Unbundling Databases -- Aiming for Correctness -- Doing the Right Thing -- Summary