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Titlebook: Cosmos DB for MongoDB Developers; Migrating to Azure C Manish Sharma Book 2018 Manish Sharma 2018 CosmosDB.GraphDB.MongoDB.DocumentDB.Table

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發(fā)表于 2025-3-21 19:13:46 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Cosmos DB for MongoDB Developers
副標題Migrating to Azure C
編輯Manish Sharma
視頻videohttp://file.papertrans.cn/239/238970/238970.mp4
概述First book covering the MongoDB API of Cosmos DB.Discusses integration of Azure Cosmos DB with Spark.Covers advanced features such as the multi-homing API and TTL using the Cosmos DB for MongoDB API
圖書封面Titlebook: Cosmos DB for MongoDB Developers; Migrating to Azure C Manish Sharma Book 2018 Manish Sharma 2018 CosmosDB.GraphDB.MongoDB.DocumentDB.Table
描述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.Migra
出版日期Book 2018
關鍵詞CosmosDB; GraphDB; MongoDB; DocumentDB; TableStorage; Azure; NoSql; Gremlin; Neo4J; Microsoft
版次1
doihttps://doi.org/10.1007/978-1-4842-3682-6
isbn_softcover978-1-4842-3681-9
isbn_ebook978-1-4842-3682-6
copyrightManish Sharma 2018
The information of publication is updating

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發(fā)表于 2025-3-21 23:39:37 | 只看該作者
Book 2018ios 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.Migra
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發(fā)表于 2025-3-22 02:33:34 | 只看該作者
lti-homing API and TTL using the Cosmos DB for MongoDB APILearn 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 expla
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Partitioning,database management systems (RDBMSs), this can occasionally be a nightmare, and it presents no less difficult a task in the realm of NoSQL too. In this chapter, you are going to learn how, using partitioning, Azure Cosmos DB scales databases.
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Hans Georg Schachtschabel als Parlamentarier to access the system, but apart from that at the main location, the system performs badly, owing to latency issues. So, how do you ensure that a database is available? How do you ensure that the database is always deployed nearest to the relevant application? And how do you achieve the lowest possible latency?
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Hans H. Nachtkamp,Gerlinde Sinnd maintain. The volume of data is often humongous and mostly unpredictable. In such cases, splitting data into multiple pieces while inserting and joining the tables during data retrieval will add excessive latency.
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Sektorstruktur und Umweltpolitikcomputing capacity available from an on-premise machine or a virtual machine in the cloud. In the cloud, having a massive compute-capacity PaaS is the most desirable option, as, in this case, one needn’t worry about scalability, performance, and availability. All of these will be provided by the clo
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