This document provides an overview of Azure Cosmos DB, a fully managed NoSQL database service. It describes key features like global distribution, high availability, and ease of development. It also outlines the supported programming languages and frameworks. Additionally, it explains the resource hierarchy including databases, collections, documents, and more. It provides details on querying data using SQL and modeling approaches. Finally, it discusses integrating with Azure Search for indexing and exploring data using the online query playground.
Build 2017 - P4010 - A lap around Azure HDInsight and Cosmos DB Open Source A...Windows Developer
Recently, we released the Spark Connector for our distributed NoSQL service – Azure Cosmos DB (formerly known as Azure DocumentDB). By connecting Apache Spark running on top Azure HDInsight to Azure Cosmos DB, you can accelerate your ability to solve fast-moving data science problems and machine learning. The Spark to Azure Cosmos DB connector efficiently exploits the native Cosmos DB managed indexes and enables updateable columns when performing analytics, push-down predicate filtering against fast-changing globally-distributed data, ranging from IoT, data science, and analytics scenarios. Come learn how you can perform blazing fast planet-scale data processing with Azure Cosmos DB and HDInsight.
Azure Cosmos DB is Microsoft’s globally-distributed database service "for managing data at planet-scale" launched in May 2017. It builds upon and extends the earlier Azure DocumentDB, which was released in 2014. It is schema-less and generally classified as a NoSQL database. Please refer git@github.com:NexThoughts/Cosmos-DB.git
Azure Cosmos DB: Features, Practical Use and Optimization "GlobalLogic Ukraine
This presentation is dedicated to Azure Cosmos DB, it's history, characteristics, tasks and solutions. The presentation deals with performance optimization, practical experience of usage and an overview of the news about Cosmos DB from Microsoft Build 2017 conference (https://build.microsoft.com).
This presentation by Andriy Gorda (Engineering Manager & Lead Software Engineer, Consultant, GlobalLogic Kharkiv) was delivered at GlobalLogic Kharkiv MS TechTalk on June 13, 2017.
Build 2017 - P4010 - A lap around Azure HDInsight and Cosmos DB Open Source A...Windows Developer
Recently, we released the Spark Connector for our distributed NoSQL service – Azure Cosmos DB (formerly known as Azure DocumentDB). By connecting Apache Spark running on top Azure HDInsight to Azure Cosmos DB, you can accelerate your ability to solve fast-moving data science problems and machine learning. The Spark to Azure Cosmos DB connector efficiently exploits the native Cosmos DB managed indexes and enables updateable columns when performing analytics, push-down predicate filtering against fast-changing globally-distributed data, ranging from IoT, data science, and analytics scenarios. Come learn how you can perform blazing fast planet-scale data processing with Azure Cosmos DB and HDInsight.
Azure Cosmos DB is Microsoft’s globally-distributed database service "for managing data at planet-scale" launched in May 2017. It builds upon and extends the earlier Azure DocumentDB, which was released in 2014. It is schema-less and generally classified as a NoSQL database. Please refer git@github.com:NexThoughts/Cosmos-DB.git
Azure Cosmos DB: Features, Practical Use and Optimization "GlobalLogic Ukraine
This presentation is dedicated to Azure Cosmos DB, it's history, characteristics, tasks and solutions. The presentation deals with performance optimization, practical experience of usage and an overview of the news about Cosmos DB from Microsoft Build 2017 conference (https://build.microsoft.com).
This presentation by Andriy Gorda (Engineering Manager & Lead Software Engineer, Consultant, GlobalLogic Kharkiv) was delivered at GlobalLogic Kharkiv MS TechTalk on June 13, 2017.
Why MongoDB over other Databases - HabilelabsHabilelabs
MongoDB is the faster-growing database. It is an open-source document and leading NoSQL database with the scalability and flexibility that you want with the querying and indexing that you need. In this Document, I presented why to choose MongoDB is over another database.
Introduction to CosmosDB - Azure Bootcamp 2018Josh Carlisle
[Session Abstract] Cosmos DB is a globally distributed, multi-model, Serverless, NoSQL database solution that runs on Microsoft Azure. With guaranteed SLAs, various consistency models, and support for multiple APIs, Cosmos DB can have many advantages over common relational database solutions. However, the shift to NoSQL in addition to the numerous configuration options available in Cosmos DB can be a challenge for traditional relational database developers. In this talk, we will take an existing application built on a traditional relational database and update the solution to take advantage of Cosmos DB. Along the way, we will have many decisions to make including which API we should use, how best to model our data, which consistency model to use, and how our data should be indexed, partitioned, and organized. By the end of the talk you should have familiarity with the decisions you will need to make to successfully implement your own solutions on Cosmos DB.
MongoDB Introduction talk at Dr Dobbs Conference, MongoDB Evenings at Bangalo...Prasoon Kumar
MongoDB is a leading nosql database. It is horizonatally scalable, document datastore. In this introduction given at Dr Dobbs Conference, Bangalore and Pune in April 2014, I show schema design with an example blog application and Python code snippets. I delivered the same in the maiden MongoDB Evening event at Delhi and Gurgaon in May 2014.
When constructing a data model for your MongoDB collection for CMS, there are various options you can choose from, each of which has its strengths and weaknesses. The three basic patterns are:
1.Store each comment in its own document.
2.Embed all comments in the “parent” document.
3.A hybrid design, stores comments separately from the “parent,” but aggregates comments into a small number of documents, where each contains many comments.
Code sample and wiki documentation is available on https://github.com/prasoonk/mycms_mongodb/wiki.
Cloud storage is one of the primary service offered by almost all the leading cloud service providers. This presentation looks into the options of Cloud storage in Azure, AWS and Google Cloud platform.
Colombo Cloud User Meetup
NoSQL datastores fall under the following categories: Key-value stores, document databases, column-family stores and graph databases. The traditional TPC-* tests are not sufficient for these heterogeneous database systems. MongoDB, CouchDB, Cassandra, HBase, Memcaches etc belong to one of 4 families and a common workload can be generated by ycsb to simulate your usecase and benchmark them.
Move your on prem data to a lake in a Lake in CloudCAMMS
With the boom in data; the volume and its complexity, the trend is to move data to the cloud. Where and How do we do this? Azure gives you the answer. In this session, I will give you an introduction to Azure Data Lake and Azure Data Factory, and why they are good for the type of problem we are talking about. You will learn how large datasets can be stored on the cloud, and how you could transport your data to this store. The session will briefly cover Azure Data Lake as the modern warehouse for data on the cloud,
Data is as critical as ever. Storage costs are lower but we have more and more data to store. This is where Microsoft Azure Data Storage solutions come in. This slide deck provides an overview of the most important data storage options available in Azure.
Note: I did not create this deck. I instead combined slides from the Microsoft Azure-Readiness/DevCamp repo on GitHub (https://github.com/Azure-Readiness/DevCamp) while adding additional material from a slide deck of David Chappell's.
This talk was given at Cloud Camp Kitchener 2015.
A fotopedia presentation made at the MongoDay 2012 in Paris at Xebia Office.
Talk by Pierre Baillet and Mathieu Poumeyrol.
French Article about the presentation:
http://www.touilleur-express.fr/2012/02/06/mongodb-retour-sur-experience-chez-fotopedia/
Video to come.
Relational databases are used extensively in many applications and systems, but they are not always the best data store solution to the problem at hand. In this session we discuss the limitations of RDBMS and show which NoSQL solutions can be used to overcome these limitations. We also cover migration topics, such as how to add NoSQL databases without adding complexity to your development and operations.
Why MongoDB over other Databases - HabilelabsHabilelabs
MongoDB is the faster-growing database. It is an open-source document and leading NoSQL database with the scalability and flexibility that you want with the querying and indexing that you need. In this Document, I presented why to choose MongoDB is over another database.
Introduction to CosmosDB - Azure Bootcamp 2018Josh Carlisle
[Session Abstract] Cosmos DB is a globally distributed, multi-model, Serverless, NoSQL database solution that runs on Microsoft Azure. With guaranteed SLAs, various consistency models, and support for multiple APIs, Cosmos DB can have many advantages over common relational database solutions. However, the shift to NoSQL in addition to the numerous configuration options available in Cosmos DB can be a challenge for traditional relational database developers. In this talk, we will take an existing application built on a traditional relational database and update the solution to take advantage of Cosmos DB. Along the way, we will have many decisions to make including which API we should use, how best to model our data, which consistency model to use, and how our data should be indexed, partitioned, and organized. By the end of the talk you should have familiarity with the decisions you will need to make to successfully implement your own solutions on Cosmos DB.
MongoDB Introduction talk at Dr Dobbs Conference, MongoDB Evenings at Bangalo...Prasoon Kumar
MongoDB is a leading nosql database. It is horizonatally scalable, document datastore. In this introduction given at Dr Dobbs Conference, Bangalore and Pune in April 2014, I show schema design with an example blog application and Python code snippets. I delivered the same in the maiden MongoDB Evening event at Delhi and Gurgaon in May 2014.
When constructing a data model for your MongoDB collection for CMS, there are various options you can choose from, each of which has its strengths and weaknesses. The three basic patterns are:
1.Store each comment in its own document.
2.Embed all comments in the “parent” document.
3.A hybrid design, stores comments separately from the “parent,” but aggregates comments into a small number of documents, where each contains many comments.
Code sample and wiki documentation is available on https://github.com/prasoonk/mycms_mongodb/wiki.
Cloud storage is one of the primary service offered by almost all the leading cloud service providers. This presentation looks into the options of Cloud storage in Azure, AWS and Google Cloud platform.
Colombo Cloud User Meetup
NoSQL datastores fall under the following categories: Key-value stores, document databases, column-family stores and graph databases. The traditional TPC-* tests are not sufficient for these heterogeneous database systems. MongoDB, CouchDB, Cassandra, HBase, Memcaches etc belong to one of 4 families and a common workload can be generated by ycsb to simulate your usecase and benchmark them.
Move your on prem data to a lake in a Lake in CloudCAMMS
With the boom in data; the volume and its complexity, the trend is to move data to the cloud. Where and How do we do this? Azure gives you the answer. In this session, I will give you an introduction to Azure Data Lake and Azure Data Factory, and why they are good for the type of problem we are talking about. You will learn how large datasets can be stored on the cloud, and how you could transport your data to this store. The session will briefly cover Azure Data Lake as the modern warehouse for data on the cloud,
Data is as critical as ever. Storage costs are lower but we have more and more data to store. This is where Microsoft Azure Data Storage solutions come in. This slide deck provides an overview of the most important data storage options available in Azure.
Note: I did not create this deck. I instead combined slides from the Microsoft Azure-Readiness/DevCamp repo on GitHub (https://github.com/Azure-Readiness/DevCamp) while adding additional material from a slide deck of David Chappell's.
This talk was given at Cloud Camp Kitchener 2015.
A fotopedia presentation made at the MongoDay 2012 in Paris at Xebia Office.
Talk by Pierre Baillet and Mathieu Poumeyrol.
French Article about the presentation:
http://www.touilleur-express.fr/2012/02/06/mongodb-retour-sur-experience-chez-fotopedia/
Video to come.
Relational databases are used extensively in many applications and systems, but they are not always the best data store solution to the problem at hand. In this session we discuss the limitations of RDBMS and show which NoSQL solutions can be used to overcome these limitations. We also cover migration topics, such as how to add NoSQL databases without adding complexity to your development and operations.
Azure DocumentDB for Healthcare IntegrationBizTalk360
In this session,
You will learn what the series is about, and see what we want to accomplish.
For this session you will be learning about Azure DocumentDB, its features and capabilities.
You will learn how to create a DocumentDB database and configure it to support CRUD operations.
You will also learn about the two API’s provided for DocumentDB
You will learn how DocumentDB can be leveraged as a repository for HL7 documents
We will take a look at using DocumentDB with both API and Logic apps
Azure Days 2019: Business Intelligence auf Azure (Marco Amhof & Yves Mauron)Trivadis
In dieser Session stellen wir ein Projekt vor, in welchem wir ein umfassendes BI-System mit Hilfe von Azure Blob Storage, Azure SQL, Azure Logic Apps und Azure Analysis Services für und in der Azure Cloud aufgebaut haben. Wir berichten über die Herausforderungen, wie wir diese gelöst haben und welche Learnings und Best Practices wir mitgenommen haben.
Introduction to Cosmos DB Presentation.pptxKnoldus Inc.
We will give an introduce Azure Cosmos DB and will cover the following topic.
* What is cosmos DB
* Why should we use cosmos db
* What are the benefits of cosmos db
* Comparison with other databases
* Cons/Pros of cosmos db
* And how we can access it
The event, held on 22nd April 2017, was part of the Global Azure Boot Camp and covered Microsoft curriculum on the following topics:
- Azure SQL Database
- JSON Support
- Encryption
- Temporal tables
- Database Advisor
- Query Performance Insight
- Dynamic Data Masking
https://techspark.mt/global-azure-bootcamp-22nd-april-2017/
DocumentDB is a powerful NoSQL solution. It provides elastic scale, high performance, global distribution, a flexible data model, and is fully managed. If you are looking for a scaled OLTP solution that is too much for SQL Server to handle (i.e. millions of transactions per second) and/or will be using JSON documents, DocumentDB is the answer.
QuerySurge Slide Deck for Big Data Testing WebinarRTTS
This is a slide deck from QuerySurge's Big Data Testing webinar.
Learn why Testing is pivotal to the success of your Big Data Strategy .
Learn more at www.querysurge.com
The growing variety of new data sources is pushing organizations to look for streamlined ways to manage complexities and get the most out of their data-related investments. The companies that do this correctly are realizing the power of big data for business expansion and growth.
Learn why testing your enterprise's data is pivotal for success with big data, Hadoop and NoSQL. Learn how to increase your testing speed, boost your testing coverage (up to 100%), and improve the level of quality within your data warehouse - all with one ETL testing tool.
This information is geared towards:
- Big Data & Data Warehouse Architects,
- ETL Developers
- ETL Testers, Big Data Testers
- Data Analysts
- Operations teams
- Business Intelligence (BI) Architects
- Data Management Officers & Directors
You will learn how to:
- Improve your Data Quality
- Accelerate your data testing cycles
- Reduce your costs & risks
- Provide a huge ROI (as high as 1,300%)
Best practices on Building a Big Data Analytics Solution (SQLBits 2018 Traini...Michael Rys
From theory to implementation - follow the steps of implementing an end-to-end analytics solution illustrated with some best practices and examples in Azure Data Lake.
During this full training day we will share the architecture patterns, tooling, learnings and tips and tricks for building such services on Azure Data Lake. We take you through some anti-patterns and best practices on data loading and organization, give you hands-on time and the ability to develop some of your own U-SQL scripts to process your data and discuss the pros and cons of files versus tables.
This were the slides presented at the SQLBits 2018 Training Day on Feb 21, 2018.
Desarrollando Microservicios con DAPR - Marzo 2020Fernando Mejía
Microservicios, beneficios y desafíos, explicados con Tesla como Ejemplo
K8s, el nuevo servidor de aplicaciones
Serverless, un futuro brillante
Dapr, el nuevo framework para aplicaciones Cloud Native
Demos Dapr
Cierre y Conclusiones
La agilidad y disponibilidad de la nube así como las constantes demandas de velocidad de los negocios, han provocado el surgimiento de aplicaciones basadas en microservicios. En esta charla veremos cómo utilizar esta arquitectura en Azure.
Arquitectura de Solución en Azure: Sitio Simple de MarketingFernando Mejía
Implementaremos una arquitectura de soluciones de azure . En esta ocasión haremos la arquitectura de un CMS simple de marketing con componentes como webapps, cdn, azure sql, redis cache y application insights.
Como se traduce IAAS y PAAS a Azure, ventajas y escenarios reales en los cuales puedes aplicara cada uno de estos en Azure. Además de esto mostraremos como poder usar Azure durante 12 meses con crédito de prueba para probar soluciones.
DevOps Practices and how to implement it using VSTSFernando Mejía
¿Qué es DevOps? ¿Por qué invertir esfuerzos en prácticas DevOps? Cuales son sus ventajas y como implementarlo fácilmente usando visual studio team services.
Are you trying to get some new leads for your business? Do you know in which stage are you loosing them? In this session (workshop format) you will learn how to build and setup a Lead Generation Channel from scratch leveraging your Microsoft Bizspark/Azure perks. To whom is this for
This session is designed for technical and business founders, CTOs, CEOs and Devs.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
10. Azure CosmosDB
Azure CosmosDB 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.
11. CosmosDB Development
Developing solutions
against DocumentDB
is designed to be
simple and
“approachable”,
meaning you can start
leveraging existing
programming skills
from the beginning—
without needing to
learn another
proprietary language.
12. 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.
14. 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.
15. 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.
17. 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
18. Modeling
• Normalizing is
referred to as
referencing
• Denormalizing is
referred to as
embedding
• In some scenarios a
hybrid model is
acceptable, based
on performance
Modeling is the technique of creating a logical connections and
relationships between data sources.
referenced
embedded
19. Azure Search
Azure Search is
“delegated” cloud-
based search service
that can be
populated and
indexed to provide
ultra-high
performing queries
against data
sources, including
Azure DocumentDB.
20. Azure Search Indexing
• Ultra-fast performance
• Can be managed at a
granular level
• Supports both
rudimentary and
extended datatypes
• Can be managed
programmatically
21. Exploring Data
Before you start working with
live data, or restructure and re-
modeling your data schemas
and relationships, its often
helpful to “practice” in a safe
environment. The Azure
DocumentDB Query
Playground has been designed
for this purpose and located at:
https://www.documentdb.com/
sql/demo
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.
Programming against DocumentDB is simple, approachable, and does not require you to adopt new tools or adhere to custom extensions to JSON or JavaScript. You can access all of the database functionality including CRUD, query, and JavaScript processing over a simple RESTful HTTP interface. DocumentDB embraces existing formats, languages, and standards while offering high value database capabilities on top of them.
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.
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”.
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.
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.
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.
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.
When modeling data stored in DocumentDB document stores entities are always exposed as self-contained documents represented in JSON. Unlike relational database scenarios, DocumentDB best practice concepts maintain that everything gets stored as “denormalized” and content gets embed via queries and modeled queries into a single document.
Azure Search can be integrated into your development ecosystems to add extremely performant search experience to any scenario, including web and mobile applications. Azure Search allows add a these experiences to your applications using a simple REST API or .NET SDK without managing search infrastructure or becoming an expert in search, and supports querying and indexing against all common datatypes and structures, including geospatial and mapping data.
The mechanism used by Azure Search to support ultra-fast querying is based on the concept of creating and managing indexes. An index is a persistent store of documents (and other constructs) identified by the Azure Search service. A document is a single unit of searchable data in your index. In Azure Search terminology, an index is conceptually similar to a table, and documents are roughly equivalent to rows in a table. Azure Search is often combined with support database storage mechanisms, such as SQL Server, Azure Blob Storage, and Azure DocumentDB to provide enhanced search experiences. Just as with Azure DocumentDB scenarios, Azure Search indexes and tuning can be managed via REST-ful HTTP calls or supported SDKs.
To get familiar with DocumentDB querying techniques and practice writing and adapting classic SELECT, FROM and WHERE queries into more DocumentDB-centric logic visualizations, the Azure Portal provides a DocumentDB Query Playground where you can experiment with various types of queries and data sources, including de-normalized, unstructured, and geospatial sample data.
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