By Kyle Banker, Tim Hawkins, Peter Bakkum, Shaun Verch, Douglas Garrett
MongoDB in motion, 2d variation is a very revised and up to date model. It introduces MongoDB 3.0 and the document-oriented database version. This completely paced booklet supplies either the massive photograph you'll want as a developer and adequate low-level element to meet approach engineers.
MongoDB in motion, 2d version is a totally revised and up to date model. It introduces MongoDB 3.0 and the document-oriented database version. This completely paced booklet supplies either the massive photo you'll desire as a developer and adequate low-level aspect to meet approach engineers. plenty of examples may help you advance self assurance within the the most important region of knowledge modeling. You'll additionally love the deep factors of every function, together with replication, auto-sharding, and deployment.
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Additional info for MongoDB in Action (2nd Edition)
Example text
Because of their simplicity, key-value stores are extremely fast and relatively easy to scale. Relational databases are more difficult to scale, at least horizontally, but have a rich data model and a powerful query language. MongoDB is intended to be a compromise between these two designs, with useful aspects of both. The end goal is for it to be a database that scales easily, stores rich data structures, and provides sophisticated query mechanisms. 7 CSV stands for Comma-Separated Values, meaning data split into multiple fields, which are separated by commas.
8 Summary We’ve covered a lot. To summarize, MongoDB is an open source, document-based database management system. Designed for the data and scalability requirements of modern internet applications, MongoDB features dynamic queries and secondary indexes, fast atomic updates and complex aggregations, and support for replication with automatic failover and sharding for scaling horizontally. That’s a mouthful, but if you’ve read this far, you should have a good feel for all these capabilities. You’re probably itching to code.
When you query MongoDB and get results back, these will be translated into an easy-to-read data structure. The MongoDB shell uses JavaScript and gets documents in JSON, which is what we’ll use for most of our examples. We’ll discuss the BSON format extensively in later chapters. Where relational databases have tables, MongoDB has collections. In other words, MySQL (a popular relational database) keeps its data in tables of rows, while MongoDB keeps its data in collections of documents, which you can think of as a group of documents.