پایگاه دادهٔ کازموس برای توسعه‌دهندگان MongoDB: مهاجرت به کازموس DB آژور و استفاده از API MongoDB

Protocol Support and Multimodal APITable Storage API; SQL (DocumentDB) API; FROM Clause; WHERE Clause; SELECT Clause; ORDER BY Clause; Query Example; MongoDB API; Graph API; Cassandra API; Elastic Scale; Throughput; Storage; Consistency; Strong; Bounded Staleness; Session; Consistent Prefix; Eventual; Performance; Service Level Agreement (SLA); Availability SLA; Throughput SLA; Consistency SLA; Latency SLA; Conclusion; Chapter 3: Azure Cosmos DB Geo-Replication; Database Availability (DA); MongoDB Replication; Data-Bearing Nodes; Arbiter Nodes; Azure Cosmos DB Replication;Chapter 8: Migrating to Azure Cosmos DB-MongoDB APIMigration Strategies; mongoexport and mongoimport; For Linux; For Windows mongodump/mongorestore; For Linux; For Windows; BulkExecutor; Application Switch; Optimization; Conclusion; Chapter 9: Azure Cosmos DB-MongoDB API Advanced Services; Aggregation Pipeline; Spark Connector; Conclusion; Index;Intro; Table of Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Why NoSQL?; Types of NoSQL; Key-Value Pair; Columnar; Document; Graph; What to Expect from NoSQL; Atomicity; Consistency; Isolation; Durability; Consistency; Availability; Partition Tolerance; Example 1: Availability; Example 2: Consistency; NoSQL and Cloud; IaaS; PaaS; SaaS; Conclusion; Chapter 2: Azure Cosmos DB Overview; Data Model Overview; Provisioning Azure Cosmos DB; Turnkey Global Distribution; Latency; Consistency; Throughput; Availability; Reliability;Auto-Shifting Geo APIsConsistency and Global Distribution; Conclusion; Chapter 4: Indexing; Indexing in MongoDB; Single Field Index; Query Using an Index; Query Not Using an Index; Compound Index; Multikey Index; Geospatial Index; Text Index; Hashed Index; Indexing in Azure Cosmos DB; TTL Indexes; Array Indexes; Sparse Indexes; Unique Indexes; Custom Indexing; Indexing Modes; Indexing Paths; Index Kinds; Hash Indexes; Range Indexes; Geospatial Indexes; Index Precision; Data Types; Conclusion; Chapter 5: Partitioning; Sharding; Partitioning in Azure Cosmos DB; Optimizations;Selecting a Partition KeyUse Case; Evaluate Every Field to Be a Potential Partition Key; Selection of the Partition Key; Conclusion; Chapter 6: Consistency; Consistency in Distributed Databases; Consistency in MongoDB; Consistency in Azure Cosmos DB; Consistent Reads/Writes; Strong Consistency; Bounded Staleness; Session; High Throughput; Consistent Prefix; Eventual; Conclusion; Chapter 7: Sizing; Request Units (RUs); Allocation of RUs; Calculating RUs; Optimizing RU Consumption; Document Size and Complexity; Data Consistency; Indexing; Query Patterns; Conclusion;For MongoDB developers who wish to learn Azure Cosmos DB, this book will guide you in identifying the whys and hows that you can employ in your applications and help you in achieving extraordinary success. -- Learn Azure Cosmos DB and its MongoDB API with hands-on samples and advanced features such as the multi-homing API, geo-replication, custom indexing, TTL, request units (RU), consistency levels, partitioning, and much more. Each chapter explains Azure Cosmos DB’s features and functionalities by comparing it to MongoDB with coding samples. Cosmos DB for MongoDB Developers starts with an overview of NoSQL and Azure Cosmos DB and moves on to demonstrate the difference between geo-replication of Azure Cosmos DB compared to MongoDB. Along the way you’ll cover subjects including indexing, partitioning, consistency, and sizing, all of which will help you understand the concepts of read units and how this calculation is derived from an existing MongoDB’s usage. The next part of the book shows you the process and strategies for migrating to Azure Cosmos DB. You will learn the day-to-day scenarios of using Azure Cosmos DB, its sizing strategies, and optimizing techniques for the MongoDB API. This information will help you when planning to migrate from MongoDB or if you would like to compare MongoDB to the Azure Cosmos DB MongoDB API before considering the switch. What You Will Learn Migrate to MongoDB and understand its strategies Develop a sample application using MongoDB’s client driver Make use of sizing best practices and performance optimization scenarios Optimize MongoDB’s partition mechanism and indexing Who This Book Is For MongoDB developers who wish to learn Azure Cosmos DB. It specifically caters to a technical audience, working on MongoDB. Learn Azure Cosmos DB and its MongoDB API with hands-on samples and advanced features such as the multi-homing API, geo-replication, custom indexing, TTL, request units (RU), consistency levels, partitioning, and much more. Each chapter explains Azure Cosmos DB's features and functionalities by comparing it to MongoDB with coding samples. Cosmos DB for MongoDB Developers starts with an overview of NoSQL and Azure Cosmos DB and moves on to demonstrate the difference between geo-replication of Azure Cosmos DB compared to MongoDB. Along the way you'll cover subjects including indexing, partitioning, consistency, and sizing, all of which will help you understand the concepts of read units and how this calculation is derived from an existing MongoDB's usage. The next part of the book shows you the process and strategies for migrating to Azure Cosmos DB. You will learn the day-to-day scenarios of using Azure Cosmos DB, its sizing strategies, and optimizing techniques for the MongoDB API. This information will help you when planning to migrate from MongoDB or if you would like to compare MongoDB to the Azure Cosmos DB MongoDB API before considering the switch. What You Will Learn Migrate to Mongo DB and understand its strategies Develop a sample application using MongoDB's client driver Make use of sizing best practices and performance optimization scenarios Optimize MongoDB's partition mechanism and indexing Who This Book Is For MongoDB developers who wish to learn Azure Cosmos DB. It specifically caters to a technical audience, working on MongoDB.