فهرست مطالب

• Cover
• Copyright
• Table of Contents
• Foreword
• Preface
• Chapter 1. Streaming Foundations
• Turning the Database Inside Out
• Externalizing Database Features
• Use Case: Clickstream Analysis
• Context Enrichment
• Change Data Capture
• Connectors
• Summary
• Chapter 2. Stream Processing Platforms
• Stateful Transformations
• Data Pipelines
• Stream Processors
• Emulating Materialized Views in Apache Spark
• Two Types of Streams
• Summary
• Chapter 3. Serving Real-Time Data
• Real-Time Expectations
• Choosing an Analytical Data Store
• Sourcing from a Topic
• Ingestion Transformations
• OLTP Versus OLAP
• Queries Per Second and Concurrency
• Indexing
• Serving Analytical Results
• Summary
• Chapter 4. Materialized Views
• Views, Materialized Views, and Incremental Updates
• Change Data Capture
• Push Versus Pull Queries
• CDC and Upsert
• Joining Streams
• Summary
• Chapter 5. Introduction to Streaming Databases
• Identifying the Streaming Database
• SQL Expressivity
• Streaming Debuggability
• Streaming Database Implementations
• Streaming Database Architecture
• ELT with Streaming Databases
• Summary
• Chapter 6. Consistency
• A Toy Example
• Comparing Consistency Across Stream Processing Systems
• Going Beyond Eventual Consistency
• Consistency Versus Latency
• Summary
• Chapter 7. Emergence of Other Hybrid Data Systems
• Data Planes
• Hybrid Transactional/Analytical Database
• Other Hybrid Databases
• Motivations for Hybrid Systems
• The Influence of PostgreSQL on Hybrid Databases
• Near-Edge Analytics
• Next-Generation Hybrid Databases
• Summary
• Chapter 8. Zero-ETL or Near-Zero-ETL
• ETL Model
• Zero-ETL
• Near-Zero-ETL
• Lambda Architecture
• Summary
• Chapter 9. The Streaming Plane
• Data Gravity
• Components of the Streaming Plane
• Streaming Plane Infrastructure
• Operational Analytics
• Data Mesh
• Streaming Data Mesh with Streaming Plane and Streaming Databases
• Summary
• Chapter 10. Deployment Models
• Consistent Streaming Database
• Consistent Streaming Processor and RTOLAP
• Eventually Consistent OLAP Streaming Database
• Eventually Consistent Stream Processor and RTOLAP
• Eventually Consistent Stream Processor and HTAP
• ksqlDB
• Incremental View Maintenance
• Postgres Multicorn Foreign Data Wrapper
• When to Use Code-Based Stream Processors
• When to Use Lakehouse/Streamhouse Technologies
• Caching Technologies
• Where to Do Processing and Querying in General?
• Summary
• Chapter 11. Future State of Real-Time Data
• The Convergence of the Data Planes
• Graph Databases
• Vector Databases
• Incremental View Maintenance
• Data Wrapping and Postgres Multicorn
• Classical Databases
• Data Warehouses
• Lakehouse
• Conclusion
• Index
• About the Authors
• Colophon