Books
MongoDB Data Modeling and Schema Design
MongoDB has become increasingly popular as a leading NoSQL database. Its flexibility, scalability, and ease of use have made it a popular choice for many developers and businesses. MongoDB's document-based model allows for flexible storage of complex data and easy evolution of the schema.
As it turns out, data modeling is even more important for MongoDB than for relational databases, as there are no guardrails like the rules of normalization. The consequence is that the responsibility to ensure consistency, integrity, and quality shifts elsewhere.
Learn how to properly design your data model with MongoDB to avoid problems later.
Our role with this book is to make you aware of all of the possibilities, cover the pros and cons, and share use cases. This should inspire readers as they design their schemas. The book includes a recipe for a proven approach to data modeling. It is a toolbox in which we describe no less than 16 different schema design patterns for MongoDB documents.
MongoDB design patterns are reusable solutions for many of the commonly occurring use cases encountered when designing applications that leverage persistence in MongoDB.
Read MongoDB Data Modeling and Schema Design if you are a data architect or modeler who needs to expand your modeling skills to include MongoDB, or if you are a database administrator or developer who knows MongoDB but needs to expand your schema design skills.
Most of the principles in this book are applicable to other NoSQL document databases, such as Couchbase and Amazon DocumentDB.
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Neo4j Data Modeling
Neo4j is a popular graph database that has gained popularity in recent years. Its strength lies in its ability to store and query highly connected data, making it a popular choice for applications such as social networks, recommendation engines, and fraud detection. Neo4j's unique property graph model enables developers to store data as nodes and relationships, providing a rich and expressive way to model complex domains.
Read Neo4j Data Modeling if you are a data architect or modeler who needs to expand your modeling skills to include Neo4j, or if you are a database administrator or developer who knows Neo4j but needs to expand your schema design skills.
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Data Modeling and Schema Design for Elasticsearch
Elasticsearch, although primarily known as a search and analytics engine, can also be considered as a NoSQL database. It is designed to store and retrieve large volumes of structured and unstructured data in a distributed and scalable manner. Elasticsearch stores data in a schema-less JSON format, allowing for flexible and dynamic data modeling. It provides powerful indexing and querying capabilities, allowing you to search and retrieve data based on various criteria and perform aggregations for analytics purposes. With its distributed architecture and built-in replication, Elasticsearch ensures high availability and fault tolerance. It's a popular choice for applications that require fast and efficient data retrieval, real-time analytics, and horizontal scalability.
Read Elasticsearch Data Modeling and Schema Design if you are a data architect or modeler who needs to expand your modeling skills to include Elasticsearch, or if you are a database administrator or developer who knows Elasticsearch but needs to expand your schema design skills.