Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide,developers and data scientists will discover how graph analytics deliver value, whether they’re used for building dynamic network models or forecasting real-world behavior. Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patterns—from finding vulnerabilities and bottlenecksto detecting communities and improving machine learning predictions. You’ll walk through hands-on examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics. Learn how graph analytics reveal more predictive elements in today’s data Understand how popular graph algorithms work and how they’re applied Use sample code and tips from more than 20 graph algorithm examples Learn which algorithms to use for different types of questions Explore examples with working code and sample datasets for Spark and Neo4j Create an ML workflow for link prediction by combining Neo4j and Spark

Learn the fundamentals of seven essential NoSQL databases in just one week with this book. Covering MongoDB, DynamoDB, Redis, Cassandra, Neo4j, InfluxDB, and HBase, you'll explore their functionalities and practical applications. Designed to give you a working understanding of NoSQL database types, this guide helps aspiring DBAs and developers comprehend and utilize modern data solutions. What this Book will help me do Master the fundamentals of MongoDB, including high-performance, high-availability, and scaling features. Gain hands-on experience with Neo4j to perform database queries and integrate with Python and Java applications. Learn efficient querying with Redis for storage and retrieval tasks. Understand Cassandra's powerful solution for scalable and fault-tolerant systems. Get well-versed with HBase for creating tables, and reading and writing data efficiently. Author(s) Sudarshan Kadambi and Xun (Brian) Wu bring a wealth of experience in database technologies. They have worked extensively in the software development and database management fields. With their practical and concise teaching approach, the authors make complex topics accessible for readers. Who is it for? This book is ideal for budding DBAs and developers looking to understand NoSQL databases. It is particularly useful for those transitioning from relational databases who want to learn about modern database technologies. Suitable for both beginners and those with some database knowledge, it aims to bridge skill gaps and expand the reader's technical expertise.

Summary

Search is a common requirement for applications of all varieties. Elasticsearch was built to make it easy to include search functionality in projects built in any language. From that foundation, the rest of the Elastic Stack has been built, expanding to many more use cases in the proces. In this episode Philipp Krenn describes the various pieces of the stack, how they fit together, and how you can use them in your infrastructure to store, search, and analyze your data.

Preamble

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline you’ll need somewhere to deploy it, so check out Linode. With private networking, shared block storage, node balancers, and a 40Gbit network, all controlled by a brand new API you’ve got everything you need to run a bullet-proof data platform. Go to dataengineeringpodcast.com/linode to get a $20 credit and launch a new server in under a minute. For complete visibility into the health of your pipeline, including deployment tracking, and powerful alerting driven by machine-learning, DataDog has got you covered. With their monitoring, metrics, and log collection agent, including extensive integrations and distributed tracing, you’ll have everything you need to find and fix performance bottlenecks in no time. Go to dataengineeringpodcast.com/datadog today to start your free 14 day trial and get a sweet new T-Shirt. Go to dataengineeringpodcast.com to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch. Your host is Tobias Macey and today I’m interviewing Philipp Krenn about the Elastic Stack and the ways that you can use it in your systems

Interview

Introduction How did you get involved in the area of data management? The Elasticsearch product has been around for a long time and is widely known, but can you give a brief overview of the other components that make up the Elastic Stack and how they work together? Beyond the common pattern of using Elasticsearch as a search engine connected to a web application, what are some of the other use cases for the various pieces of the stack? What are the common scaling bottlenecks that users should be aware of when they are dealing with large volumes of data? What do you consider to be the biggest competition to the Elastic Stack as you expand the capabilities and target usage patterns? What are the biggest challenges that you are tackling in the Elastic stack, technical or otherwise? What are the biggest challenges facing Elastic as a company in the near to medium term? Open source as a business model: https://www.elastic.co/blog/doubling-down-on-open?utm_source=rss&utm_medium=rss What is the vision for Elastic and the Elastic Stack going forward and what new features or functionality can we look forward to?

Contact Info

@xeraa on Twitter xeraa on GitHub Website Email

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

Elastic Vienna – Capital of Austria What Is Developer Advocacy? NoSQL MongoDB Elasticsearch Cassandra Neo4J Hazelcast Apache Lucene Logstash Kibana Beats X-Pack ELK Stack Metrics APM (Application Performance Monitoring) GeoJSON Split Brain Elasticsearch Ingest Nodes PacketBeat Elastic Cloud Elasticon Kibana Canvas SwiftType

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA Support Data Engineering Podcast

Summary

As software lifecycles move faster, the database needs to be able to keep up. Practices such as version controlled migration scripts and iterative schema evolution provide the necessary mechanisms to ensure that your data layer is as agile as your application. Pramod Sadalage saw the need for these capabilities during the early days of the introduction of modern development practices and co-authored a book to codify a large number of patterns to aid practitioners, and in this episode he reflects on the current state of affairs and how things have changed over the past 12 years.

Preamble

Hello and welcome to the Data Engineering Podcast, the show about modern data infrastructure When you’re ready to launch your next project you’ll need somewhere to deploy it. Check out Linode at dataengineeringpodcast.com/linode and get a $20 credit to try out their fast and reliable Linux virtual servers for running your data pipelines or trying out the tools you hear about on the show. Go to dataengineeringpodcast.com to subscribe to the show, sign up for the newsletter, read the show notes, and get in touch. You can help support the show by checking out the Patreon page which is linked from the site. To help other people find the show you can leave a review on iTunes, or Google Play Music, and tell your friends and co-workers Your host is Tobias Macey and today I’m interviewing Pramod Sadalage about refactoring databases and integrating database design into an iterative development workflow

Interview

Introduction How did you get involved in the area of data management? You first co-authored Refactoring Databases in 2006. What was the state of software and database system development at the time and why did you find it necessary to write a book on this subject? What are the characteristics of a database that make them more difficult to manage in an iterative context? How does the practice of refactoring in the context of a database compare to that of software? How has the prevalence of data abstractions such as ORMs or ODMs impacted the practice of schema design and evolution? Is there a difference in strategy when refactoring the data layer of a system when using a non-relational storage system? How has the DevOps movement and the increased focus on automation affected the state of the art in database versioning and evolution? What have you found to be the most problematic aspects of databases when trying to evolve the functionality of a system? Looking back over the past 12 years, what has changed in the areas of database design and evolution?

How has the landscape of tooling for managing and applying database versioning changed since you first wrote Refactoring Databases? What do you see as the biggest challenges facing us over the next few years?

Contact Info

Website pramodsadalage on GitHub @pramodsadalage on Twitter

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Links

Database Refactoring

Website Book

Thoughtworks Martin Fowler Agile Software Development XP (Extreme Programming) Continuous Integration

The Book Wikipedia

Test First Development DDL (Data Definition Language) DML (Data Modification Language) DevOps Flyway Liquibase DBMaintain Hibernate SQLAlchemy ORM (Object Relational Mapper) ODM (Object Document Mapper) NoSQL Document Database MongoDB OrientDB CouchBase CassandraDB Neo4j ArangoDB Unit Testing Integration Testing OLAP (On-Line Analytical Processing) OLTP (On-Line Transaction Processing) Data Warehouse Docker QA==Quality Assurance HIPAA (Health Insurance Portability and Accountability Act) PCI DSS (Payment Card Industry Data Security Standard) Polyglot Persistence Toplink Java ORM Ruby on Rails ActiveRecord Gem

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA Support Data Engineering Podcast

"Learning Neo4j 3.x" provides a comprehensive introduction to the world of graph databases, focusing on practical usage of Neo4j. This book guides you through the fundamentals, from installation and modeling to advanced features including security and optimization. You'll gain the skills to harness Neo4j for effective data management and visualization. What this Book will help me do Understand the basics of graph databases and how to use them effectively in real-world scenarios. Master the Cypher query language to query and manipulate graph data powerfully and intuitively. Learn to implement and optimize advanced graph techniques using the APOC library. Develop the ability to extend Neo4j's core functionality using available plugins and advanced extensions. Acquire skills to design and deploy scalable, secure enterprise-grade graph database solutions. Author(s) Jerome Baton and None Van Bruggen are experienced Neo4j specialists who share a passion for making complex technical concepts accessible. Jerome brings years of real-world experience in graph database applications, while None contributes expertise in data modeling and visualization. Together, they provide clear, focused insights with practical examples and hands-on guidance. Who is it for? This book is tailored for developers looking to extend their knowledge with graph databases to take on modern connected data challenges. It is suitable for those new to Neo4j, including beginners with databases, and will serve as a valuable guide for professionals aiming to deepen their expertise in data storage and query optimization using Neo4j.

This book is your introduction in the world of graph databases, and the benefits they can bring to your applications. Neo4j is the most established graph database on the market, and it's always improving to bring more of its benefits to you. Beginning Neo4j will take you from the installation of Neo4j through to building a full application with Neo4j at its heart, and everything in between. Using this book, you'll get everything up and running, and then learn how to use Neo4j to build up recommendations, relationships, and calculate the shortest route between two locations. With example data models, and an application putting everything together, this book will give you everything you need to really get started with Neo4j. Neo4j is being used by social media and ecommerce industry giants. You can take advantage of Neo4j's powerful features and benefits - add Beginning Neo4j to your library today.

Neo4j Graph Data Modelling provides practical guidance in designing and implementing graph databases using Neo4j. This book walks you through modeling concepts, database evolution, and performance optimization. You'll learn how to model real-world domains, write Cypher queries, and adapt your database as requirements change. What this Book will help me do Model data effectively using Neo4j to represent complex relationships. Translate real-world problems into graph database designs efficiently. Write optimized Cypher queries to retrieve and manipulate data. Improve database performance through thoughtful design practices. Adapt and evolve databases seamlessly as application needs change. Author(s) Mahesh K Lal is an experienced developer and database specialist with a deep understanding of graph data modeling. With a focus on practical and accessible instruction, Mahesh's work provides actionable insights into database design. Neo4j Graph Data Modelling reflects his years of hands-on experience with Neo4j. Who is it for? This book is designed for software developers and data professionals looking to explore graph databases. If you aim to effectively model real-world situations using Neo4j or optimize database queries, this guide is for you. Prior experience with databases is helpful but not mandatory.

Expand your Python web development expertise by integrating Neo4j into your applications. Through this book, you'll journey from understanding Neo4j's fundamentals to building powerful Python-based applications using tools like Flask, Py2neo, and Django. Learn how to model, query, and update graph data effectively. What this Book will help me do Gain an in-depth understanding of Neo4j installation, licensing, and tools. Master using Cypher for querying and modifying graph data models. Learn how to integrate Python with Neo4j effectively using Py2neo. Build RESTful services with Flask leveraging Neo4j for structured data. Create robust Django applications using graph-based data models with Neomodel. Author(s) Sumit Gupta is a seasoned Python developer with a strong background in graph database design and integration. He has extensive experience using Neo4j to create efficient, scalable applications for real-world problems. His hands-on approach combines practical examples with the depth of knowledge required to develop expertise. Who is it for? This book is ideal for Python developers with an interest in enhancing their applications through graph database technology. If you possess a moderate understanding of Python and wish to explore Neo4j for creating smarter, more interconnected data-driven solutions, this book is for you. You should be comfortable with basic programming concepts to fully benefit from this book.

Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. This second edition includes new code samples and diagrams, using the latest Neo4j syntax, as well as information on new functionality. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information

Dive into Neo4j and uncover how to harness its powerful capabilities in graph data analysis with the Neo4j Cookbook. Across 75 well-structured recipes, you'll learn to apply practical techniques in modeling, querying, and visualizing graph databases, enabling you to address real-world challenges efficiently. What this Book will help me do Access Neo4j from popular programming languages such as Java, Python, and Scala, enabling easier integration into your projects. Migrate data seamlessly from various data stores, including SQL and NoSQL, into Neo4j, maintaining data consistency. Use best practices for data modeling with Neo4j to optimize performance and scalability for your applications. Analyze social data from sources like Facebook and Twitter, revealing valuable insights from connections and relationships. Integrate geospatial data to enable location-based queries and nearest-point searches, opening up advanced application features. Author(s) Ankur Goel, the author of Neo4j Cookbook, is an experienced technologist with an extensive background in handling database solutions and applications. Passionate about simplifying complex systems, Ankur excels in teaching essential database concepts through clear and actionable recipes. His writing is rooted in practical insights, reflecting his hands-on experience in the industry. Who is it for? This book is ideal for developers and data engineers who currently use or plan to integrate Neo4j into their workflows. If you are migrating from a traditional database system or delving into graph databases for the first time, this book offers structured guidance. Readers should have a fundamental understanding of programming and familiarity with database concepts for the best experience. It caters to individuals aiming to build or enhance data-driven applications using Neo4j's robust graph modeling.

NoSQL was developed to overcome the limitations of relational databases in the largest Web applications at companies such as Google, Yahoo and Facebook. As it is applied more widely, developers are finding that it can simplify scalability while requiring far less coding and management overhead. However, NoSQL requires fundamentally different approaches to database design and modeling, and many conventional relational techniques lead to suboptimal results. NoSQL for Mere Mortals is an easy, practical guide to succeeding with NoSQL in your environment. Following the classic, best-selling format pioneered in SQL Queries for Mere Mortals, enterprise database expert Dan Sullivan guides you step-by-step through choosing technologies, designing high-performance databases, and planning for long-term maintenance. Sullivan introduces each type of NoSQL database, shows how to install and manage them, and demonstrates how to leverage their features while avoiding common mistakes that lead to poor performance and unmet requirements. He uses four popular NoSQL databases as reference models: MongoDB, a document database; Cassandra, a column family data store; Redis, a key-value database; and Neo4j, a graph database. You'll find explanations of each database's structure and capabilities, practical guidelines for choosing amongst them, and expert guidance on designing databases with them. Packed with examples, NoSQL for Mere Mortals is today's best way to master NoSQL—whether you're a DBA, developer, user, or student.

Dive into the world of graph databases with "Neo4j High Performance." This book takes you through the intricacies of designing, building, and maintaining robust and scalable graph-based systems tailored for your application's specific needs. Whether you're optimizing your database structures or exploring performance enhancements, this guide equips you with the skills to utilize Neo4j effectively. What this Book will help me do Understand the fundamentals of graph database principles and Neo4j's architecture. Learn how to design efficient graph data schemas to optimize performance. Develop the ability to customize Neo4j operations for high-traffic applications. Master advanced indexing and querying techniques to unlock the full potential of your data. Gain expertise in Neo4j's REST API and practical scenarios, including building recommendation systems. Author(s) Sonal Raj is a seasoned expert in graph databases and related technologies, specializing in Neo4j. With hands-on experience in solving complex data problems using graph systems, Sonal brings deep insights and practical usage paradigms to this book. Passionate about sharing knowledge, Sonal ensures this material bridges the gap from beginner understanding to expert application. Who is it for? This book is perfect for professionals and enthusiasts eager to excel in graph database technologies. If you're familiar with basic graph theory or have practical experience with Neo4j, you'll find this book insightful. Beginners seeking a structured introduction and advanced users pursuing optimization techniques will benefit equally. Ideal for developers aiming to scale their applications using graph data efficiently.

Get up to speed on the nuances of NoSQL databases and what they mean for your organization This easy to read guide to NoSQL databases provides the type of no-nonsense overview and analysis that you need to learn, including what NoSQL is and which database is right for you. Featuring specific evaluation criteria for NoSQL databases, along with a look into the pros and cons of the most popular options, NoSQL For Dummies provides the fastest and easiest way to dive into the details of this incredible technology. You'll gain an understanding of how to use NoSQL databases for mission-critical enterprise architectures and projects, and real-world examples reinforce the primary points to create an action-oriented resource for IT pros. If you're planning a big data project or platform, you probably already know you need to select a NoSQL database to complete your architecture. But with options flooding the market and updates and add-ons coming at a rapid pace, determining what you require now, and in the future, can be a tall task. This is where NoSQL For Dummies comes in! Learn the basic tenets of NoSQL databases and why they have come to the forefront as data has outpaced the capabilities of relational databases Discover major players among NoSQL databases, including Cassandra, MongoDB, MarkLogic, Neo4J, and others Get an in-depth look at the benefits and disadvantages of the wide variety of NoSQL database options Explore the needs of your organization as they relate to the capabilities of specific NoSQL databases Big data and Hadoop get all the attention, but when it comes down to it, NoSQL databases are the engines that power many big data analytics initiatives. With NoSQL For Dummies, you'll go beyond relational databases to ramp up your enterprise's data architecture in no time.

" Why have developers at places like Facebook and Twitter increasingly turned to graph databases to manage their highly connected big data? The short answer is that graphs offer superior speed and flexibility to get the job done. It’s time you added skills in graph databases to your toolkit. In Practical Neo4j, database expert Greg Jordan guides you through the background and basics of graph databases and gets you quickly up and running with Neo4j, the most prominent graph database on the market today. Jordan walks you through the data modeling stages for projects such as social networks, recommendation engines, and geo-based applications. The book also dives into the configuration steps as well as the language options used to create your Neo4j-backed applications. Neo4j runs some of the largest connected datasets in the world, and developing with it offers you a fast, proven NoSQL database option. Besides those working for social media, database, and networking companies of all sizes, academics and researchers will find Neo4j a powerful research tool that can help connect large sets of diverse data and provide insights that would otherwise remain hidden. Using Practical Neo4j, you will learn how to harness that power and create elegant solutions that address complex data problems. This book: Explains the basics of graph databases Demonstrates how to configure and maintain Neo4j Shows how to import data into Neo4j from a variety of sources Provides a working example of a Neo4j-based application using an array of language of options including Java, .Net, PHP, Python, Spring, and Ruby As you’ll discover, Neo4j offers a blend of simplicity and speed while allowing data relationships to maintain first-class status. That’s one reason among many that such a wide range of industries and fields have turned to graph databases to analyze deep, dense relationships. After reading this book, you’ll have a potent, elegant tool you can use to develop projects profitably and improve your career options.

Neo4j in Action is a comprehensive guide to Neo4j, aimed at application developers and software architects. Using hands-on examples, you'll learn to model graph domains naturally with Neo4j graph structures. The book explores the full power of native Java APIs for graph data manipulation and querying. About the Technology Much of the data today is highly connected--from social networks to supply chains to software dependency management--and more connections are continually being uncovered. Neo4j is an ideal graph database tool for highly connected data. It is mature, production-ready, and unique in enabling developers to simply and efficiently model and query connected data. About the Book Neo4j in Action is a comprehensive guide to designing, implementing, and querying graph data using Neo4j. Using hands-on examples, you'll learn to model graph domains naturally with Neo4j graph structures. The book explores the full power of native Java APIs for graph data manipulation and querying. It also covers Cypher, Neo4j's graph query language. Along the way, you'll learn how to integrate Neo4j into your domain-driven app using Spring Data Neo4j, as well as how to use Neo4j in standalone server or embedded modes. What's Inside Graph database patterns How to model data in social networks How to use Neo4j in your Java applications How to configure and set up Neo4j About the Reader Knowledge of Java basics is required. No prior experience with graph data or Neo4j is assumed. About the Authors Aleksa Vukotic is an architect specializing in graph data models. Nicki Watt, Dominic Fox, Tareq Abedrabbo, and Jonas Partner work at OpenCredo, a Neo Technology partner, and have been involved in many projects using Neo4j. Quotes A pragmatic programmatic tour through Neo4j’s APIs and query language. - From the Foreword by Jim Webber and Ian Robinson, Neo Technology Excellent coverage of one of the most successful NoSQL products. - Pouria Amirian, PhD, University of Oxford A great resource for rethinking your data storage using graphs in Neo4j. - Stephen Kitt, ERDF

Dive into the exciting world of graph databases with "Learning Neo4j". This book introduces you to the Neo4j graph database system, showing how graph theory can unlock new ways of organizing and querying complex datasets. Through practical examples, you will explore Neo4j's capabilities and learn to implement real-world applications using graph data models. What this Book will help me do Understand the fundamentals of graph theory and how it relates to databases. Install and set up the Neo4j graph database on local and cloud platforms. Model complex data for use in Neo4j and import various datasets into it. Implement real-world use cases, such as recommendation systems and social networks. Explore visualization tools and resources for enhancing graph database applications. Author(s) The author, None Van Bruggen, is a seasoned expert in data systems with extensive hands-on experience with Neo4j. Drawing from real-world expertise, they provide practical guidance, bridging theoretical concepts to practical utility seamlessly. None Van Bruggen's accessible writing style makes navigating the complexities of graph databases achievable and rewarding for learners. Who is it for? This book is ideal for IT professionals, database administrators, and data analysts looking to harness the power of graph databases. Readers should have a basic understanding of relational databases and data modeling concepts. Whether you're starting with Neo4j or seeking to deepen your knowledge, this book provides the guidance you need. It is particularly great for anyone interested in implementing graph data solutions in real-world scenarios.

"Learning Cypher" provides an in-depth look into Cypher, the functional query language for Neo4j, the powerful graph database. Whether you're transitioning from relational databases or exploring graph technology for the first time, this book offers practical guidance to help you write efficient, clear, and reusable queries. What this Book will help me do Master the Cypher declarative query syntax for graph databases. Write optimized Cypher queries for better application performance. Transform relational database data to graph database structures with ease. Understand the nuances of transitioning from SQL to graph paradigms. Learn the common pitfalls in Neo4j programming and how to avoid them. Author(s) Onofrio Panzarino is an experienced database developer specializing in graph technologies and Neo4j. He is passionate about teaching industry best practices to developers and has extensive experience in designing graph-based solutions. Through his approachable style, he empowers readers to excel in using graph databases effectively. Who is it for? This book is for database developers, data analysts, and software engineers who want to expand their knowledge into graph databases. If you work with large-scale connected data or are transitioning from SQL to a graph model, this book is ideal for you. Prior experience with any database query language will be helpful. The book is also suitable for students and professionals looking to integrate graph technology into their projects.

Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build a database that can adapt as your business evolves, this book shows you how to apply the schema-free graph model to real-world problems. Learn how different organizations are using graph databases to outperform their competitors. With this book’s data modeling, query, and code examples, you’ll quickly be able to implement your own solution. Model data with the Cypher query language and property graph model Learn best practices and common pitfalls when modeling with graphs Plan and implement a graph database solution in test-driven fashion Explore real-world examples to learn how and why organizations use a graph database Understand common patterns and components of graph database architecture Use analytical techniques and algorithms to mine graph database information

The need to handle increasingly larger data volumes is one factor driving the adoption of a new class of nonrelational “NoSQL” databases. Advocates of NoSQL databases claim they can be used to build systems that are more performant, scale better, and are easier to program. NoSQL Distilled is a concise but thorough introduction to this rapidly emerging technology. Pramod J. Sadalage and Martin Fowler explain how NoSQL databases work and the ways that they may be a superior alternative to a traditional RDBMS. The authors provide a fast-paced guide to the concepts you need to know in order to evaluate whether NoSQL databases are right for your needs and, if so, which technologies you should explore further. The first part of the book concentrates on core concepts, including schemaless data models, aggregates, new distribution models, the CAP theorem, and map-reduce. In the second part, the authors explore architectural and design issues associated with implementing NoSQL. They also present realistic use cases that demonstrate NoSQL databases at work and feature representative examples using Riak, MongoDB, Cassandra, and Neo4j. In addition, by drawing on Pramod Sadalage’s pioneering work, NoSQL Distilled shows how to implement evolutionary design with schema migration: an essential technique for applying NoSQL databases. The book concludes by describing how NoSQL is ushering in a new age of Polyglot Persistence, where multiple data-storage worlds coexist, and architects can choose the technology best optimized for each type of data access.

Data is getting bigger and more complex by the day, and so are the choices in handling that data. As a modern application developer you need to understand the emerging field of data management, both RDBMS and NoSQL. Seven Databases in Seven Weeks takes you on a tour of some of the hottest open source databases today. In the tradition of Bruce A. Tate's Seven Languages in Seven Weeks, this book goes beyond your basic tutorial to explore the essential concepts at the core each technology. Redis, Neo4J, CouchDB, MongoDB, HBase, Riak and Postgres. With each database, you'll tackle a real-world data problem that highlights the concepts and features that make it shine. You'll explore the five data models employed by these databases-relational, key/value, columnar, document and graph-and which kinds of problems are best suited to each. You'll learn how MongoDB and CouchDB are strikingly different, and discover the Dynamo heritage at the heart of Riak. Make your applications faster with Redis and more connected with Neo4J. Use MapReduce to solve Big Data problems. Build clusters of servers using scalable services like Amazon's Elastic Compute Cloud (EC2). Discover the CAP theorem and its implications for your distributed data. Understand the tradeoffs between consistency and availability, and when you can use them to your advantage. Use multiple databases in concert to create a platform that's more than the sum of its parts, or find one that meets all your needs at once. Seven Databases in Seven Weeks will take you on a deep dive into each of the databases, their strengths and weaknesses, and how to choose the ones that fit your needs. What You Need: To get the most of of this book you'll have to follow along, and that means you'll need a *nix shell (Mac OSX or Linux preferred, Windows users will need Cygwin), and Java 6 (or greater) and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.