Azure document db/Cosmos DB
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This document provides an introduction to Azure DocumentDB, a NoSQL database service. It begins with an overview of the differences between SQL and NoSQL databases, focusing on how DocumentDB is a non-relational, horizontally scalable database that uses JSON documents. It then describes key aspects of DocumentDB such as its supported languages and frameworks, its HTTP REST API, how data is stored in JSON documents, and its resources and hierarchical structure. The document also covers querying data using SQL and the services' indexing and consistency capabilities.
![DocumentDB in One Slide
9
• Simple HTTP RESTful model.
• Access can be via any client that supports
HTTP. Libraries for; Node, .NET, Python, JS
• All resources are uniquely addressable by
a URI.
• Partitioned for scale out and replicated
for HA. Tunable indexing & consistency
• Granular access control through item
level permissions
• Attachments stored in Azure Blobs and
support document lifecycle.
• T-SQL like programmability.
• Customers buy storage and throughput
capacity basis at account level
/dbs/{id} /colls/{id} /docs/{id} /attachments/{id}
/sprocs/{id}
/triggers/{id}
/functions/{id}
/users/{id}
POST
Item
resource TenantFeed
URI
PUT
Item
resource
Item
URI
DELETE
Item
URI
GET TenantFeed Or Item
URI
Create a new resource
/Execute a sprocs/trigger/query
Replace an existing resource
Delete an existing resource
Read/Query an existing
resource
POST http://myaccount.documents.azure.net/dbs
{ "name":"My Company Db"}
...
[201 Created]
{
“id": "My Company Db",
“_rid": "UoEi5w==",
“_self": "dbs/UoEi5w==/",
“_colls": "colls/",
“_users": "users/"
}](https://image.slidesharecdn.com/azuredocumentdb-170521142122/85/Azure-document-db-Cosmos-DB-9-320.jpg)
Azure document db/Cosmos DB
- 1. INTRODUCTION TO AZURE DOCUMENT DB Mohit Chhabra Senior Software Engineer Harman International AzureGuy.in
- 3. SQL • RDBMS • SCALE UP/Horizontally Scalable • Structured or Schema • Atomic Transaction • Difficult for programmer • Eg. CAR Disassembled in and reassembled when required. NOSQL • NonRelational • Scale OUT/Horizontally Scalable • Semi or unstructured data • EVENTUAL CONSISTENCY • Easy for Programmers • Eg. Park a car in parking Comparison B/W SQL & NO-SQL
- 4. NOSQL DOCUMENT BASED- DOCUMENT DB/Cassandra Graph – Neo4j, SAP HANA Key Value Pair –Redis, Azure Storage Column Based- Cassandra Type of NOSQL
- 7. Azure DocumentDB Azure DocumentDB is a fully managed NoSQL “database as a service” built for ultra- fast and predictable performance, high availability, elastic scaling, and global distribution, and is especially focused on ease of development.
- 8. Supported Languages & Frameworks • Node.js • .NET • Python • Java • REST • SQL Tools, SDKs, and standards-based interfaces are available for DocumentDB development with powerful support for querying against most datatypes, even geospatial.
- 9. DocumentDB in One Slide 9 • Simple HTTP RESTful model. • Access can be via any client that supports HTTP. Libraries for; Node, .NET, Python, JS • All resources are uniquely addressable by a URI. • Partitioned for scale out and replicated for HA. Tunable indexing & consistency • Granular access control through item level permissions • Attachments stored in Azure Blobs and support document lifecycle. • T-SQL like programmability. • Customers buy storage and throughput capacity basis at account level /dbs/{id} /colls/{id} /docs/{id} /attachments/{id} /sprocs/{id} /triggers/{id} /functions/{id} /users/{id} POST Item resource TenantFeed URI PUT Item resource Item URI DELETE Item URI GET TenantFeed Or Item URI Create a new resource /Execute a sprocs/trigger/query Replace an existing resource Delete an existing resource Read/Query an existing resource POST http://myaccount.documents.azure.net/dbs { "name":"My Company Db"} ... [201 Created] { “id": "My Company Db", “_rid": "UoEi5w==", “_self": "dbs/UoEi5w==/", “_colls": "colls/", “_users": "users/" }
- 10. The DocumentDB Data Model 1 0 All data is stored in JSON Documents Object created in code Object saved in Database
- 11. Azure DocumentDB Resources • Database • User • Collection • Stored Procedure • Trigger • User-defined Function (UDF) • Document • Attachment
- 12. Resource Hierarchy Database A database is a logical container of document storage partitioned across collections. It is also a users container. User The logical namespace for scoping permissions. Permission An authorization token associated with a user for access to a specific resource. Collection A collection is a container of JSON documents and the associated JavaScript application logic.
- 13. Resource Hierarchy Stored Procedure Application logic written in JavaScript which is registered with a collection and transactionally executed within the database engine. Trigger Application logic written in JavaScript executed before or after either an insert, replace or delete operation. UDF Application logic written in JavaScript. UDFs enable you to model a custom query operator and thereby extend the core DocumentDB query language. Document Arbitrary user-defined JSON content. By default, no schema needs to be defined nor do secondary indices need to be provided for all the documents added to a collection.
- 14. Resource Associations ACCOUNT ACCOUNT ACCOUNT COLLECTION COLLECTION COLLECTION DATABASEDATABASE DATABASE DATABASEDATABASE DATABASE DOCUMENTS DOCUMENTS DOCUMENTS DOCUMENTS
- 15. Querying Data Azure DocumentDB supports querying of documents using a familiar SQL (Structured Query Language) over hierarchical JSON documents. • SELECT, FROM, and WHERE statements • HAVING and ORDER BY statements • Full Geospatial and Geometry support, such as ST_DISTANCE and ST_WITHIN
Editor's Notes
- #8: Azure DocumentDB is schema-free and combines rich and familiar SQL query capabilities with consistent low latencies on JSON-based data models, targeting solutions for web, mobile, gaming, and IoT. Since DocumentDB is schema agnostic, it makes it extremely easy to adjust and adapt data models on the fly as business logic and application scenarios change. With DocumentDB you no longer have to deploy constant updates to the data-tier and worry about managing schema and relationships. All content in DocumentDB is automatically indexed, which makes it possible to query data across entire structures at any time. The term “NoSQL” is more of a marketing buzzword, and actual means “no requirement for entity relationships and secondary indexing” in order to query information.
- #9: Since DocumentDB is a JSON-based storage mechanism, accessing and interacting with data can be accomplished through most standards-based interfaces, as well as robust toolsets and SDKs. Although native Universal Windows Platform support is not currently available, support for virtually any other development scenario is available. Deeper level features of are currently exposed via JavaScript, such as stored procedures, triggers and user defined functions (UDFs) making it easy for developers to write application logic that can be packaged and executed directly on database storage partitions.
- #12: To make sure specific concepts are understood, its helpful to review terminology used by DocumentDB documentation and supporting concepts. Although many of these terms and concepts apply to other data storage technologies, there are often differences in the way these terms apply to Azure DocumentDB in practical scenarios. In Azure DocumentDB systems, all elements of the hierarchy are referred to as “resources”.
- #13: Most terms used in the context of Azure DocumentDB are similar, or at least conceptual similar to terms used in both object-oriented and relational database strategies, however the scope and design of certain elements differs in exact implementation. For example an Azure DocumentDB “Collection” can span multiple servers and partitions and are the primary entity of DocumentDB “groupings”. The terms “database” and “container” are often used synonymously, as the term database is more conceptual than physical.
- #14: Similar to the terms container and database, the DocumentDB term “document” is often confusing to new developers, as “document” more commonly means a “file-based” item, such as a PDF or Word document, Excel spreadsheet, PowerPoint slide deck, or even a text file. The term document in DocumentDB-speak is actually a JSON-based representation of data, and only optionally contains binary data. To get a better picture of what a document “looks like” in DocumentDB terms, imagine a single record from a relational database formatted as a JSON object. Although optional, attachments are also supported to store binary data.
- #15: The database entities that DocumentDB manages are referred to as resources. Each resource is uniquely identified by a logical URI. You can interact with the resources using standard HTTP verbs, request/response headers and status codes, as well as object and property-based methods via the tools and SDKs.
- #16: Since DocumentDB is “schema-free” it provides automatic indexing of JSON documents without requiring explicit schema or creation of secondary indexes. If you’re familiar with legacy T-SQL or (Transactional Structured Query Language) commands you’ll be right at home querying DocumentDB content. Querying content typically consists or writing SELECT queries with option WHERE clauses and can be combined and joined across objects in the collection hierarchy.