MongoDB is the most famous and loved NoSQL database. It has many features that are easy to handle when compared to conventional RDBMS. These slides contain the basics of MongoDB.
MongoDB is the most famous and loved NoSQL database. It has many features that are easy to handle when compared to conventional RDBMS. These slides contain the basics of MongoDB.
In this presentation, Raghavendra BM of Valuebound has discussed the basics of MongoDB - an open-source document database and leading NoSQL database.
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Get Socialistic
Our website: http://valuebound.com/
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“not only SQL.”
NoSQL databases are databases store data in a format other than relational tables.
NoSQL databases or non-relational databases don’t store relationship data well.
This presentation contains the introduction to NOSQL databases, it's types with examples, differentiation with 40 year old relational database management system, it's usage, why and we should use it.
This presentation explains the major differences between SQL and NoSQL databases in terms of Scalability, Flexibility and Performance. It also talks about MongoDB which is a document-based NoSQL database and explains the database strutre for my mouse-human research classifier project.
MongoDB is an open-source document database, and the leading NoSQL database. Written in C++.
MongoDB has official drivers for a variety of popular programming languages and development environments. There are also a large number of unofficial or community-supported drivers for other programming languages and frameworks.
This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
In this presentation, Raghavendra BM of Valuebound has discussed the basics of MongoDB - an open-source document database and leading NoSQL database.
----------------------------------------------------------
Get Socialistic
Our website: http://valuebound.com/
LinkedIn: http://bit.ly/2eKgdux
Facebook: https://www.facebook.com/valuebound/
Twitter: http://bit.ly/2gFPTi8
“not only SQL.”
NoSQL databases are databases store data in a format other than relational tables.
NoSQL databases or non-relational databases don’t store relationship data well.
This presentation contains the introduction to NOSQL databases, it's types with examples, differentiation with 40 year old relational database management system, it's usage, why and we should use it.
This presentation explains the major differences between SQL and NoSQL databases in terms of Scalability, Flexibility and Performance. It also talks about MongoDB which is a document-based NoSQL database and explains the database strutre for my mouse-human research classifier project.
MongoDB is an open-source document database, and the leading NoSQL database. Written in C++.
MongoDB has official drivers for a variety of popular programming languages and development environments. There are also a large number of unofficial or community-supported drivers for other programming languages and frameworks.
This Presentation is about NoSQL which means Not Only SQL. This presentation covers the aspects of using NoSQL for Big Data and the differences from RDBMS.
Introduction to ArangoDB (nosql matters Barcelona 2012)ArangoDB Database
ArangoDB is a universal open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient sql-like query language or JavaScript/Ruby extensions.
The video is also available online:
http://2012.nosql-matters.org/bcn/speakers/
Presented in DDD Melbourne on on Sat Aug 8th 2015
Himanshu Desai, Ahmed El-Harouny & Daniel Janczak
DocumentDB, Mongo or RavenDB? If you are starting out on a new project and considering NoSQL database as an option, which one should you do choose? What if the option you choose today may not work out to be the best one for your needs?
Come and join us for this session, we will take you on a journey where we will explain each of these database on their merits and compare them and also share War stories.
http://dddmelbourne.com
We prepared a small 30 min workshop for the Dutch Java User Group to introduce MongoDB basics. This slideshow contains the mongoDB concepts, which will be workout basic in labs . The labs could be found at: http://mongodb.info/labs/
comprehensive Introduction to NoSQL solutions inside the big data landscape. Graph store? Column store? key Value store? Document Store? redis or memcache? dynamo db? mongo db ? hbase? Cloud or open source?
Demi Ben Ari - Apache Spark 101 - First Steps into distributed computing:
The world has changed, having one huge server won’t do the job, the ability to Scale Out would be your savior. Apache Spark is a fast and general engine for big data processing, with streaming, SQL, machine learning and graph processing. Showing the basics of Apache Spark and distributed computing.
Demi is a Software engineer, Entrepreneur and an International Tech Speaker.
Demi has over 10 years of experience in building various systems both from the field of near real time applications and Big Data distributed systems.
Co-Founder of the “Big Things” Big Data community and Google Developer Group Cloud.
Big Data Expert, but interested in all kinds of technologies, from front-end to backend, whatever moves data around.
MongoDB World 2019: Raiders of the Anti-patterns: A Journey Towards Fixing Sc...MongoDB
As a software adventurer, Charles “Indy” Sarrazin, has brought numerous customers through the MongoDB world, using his extensive knowledge to make sure they always got the most out of their databases.
Let us embark on a journey inside the Document Model, where we will identify, analyze and fix anti-patterns. I will also provide you with tools to ease migration strategies towards the Temple of Lost Performance!
Be warned, though! You might want to learn about design patterns before, in order to survive this exhilarating trial!
NoSQL is not a buzzword anymore. The array of non- relational technologies have found wide-scale adoption even in non-Internet scale focus areas. With the advent of the Cloud...the churn has increased even more yet there is no crystal clear guidance on adoption techniques and architectural choices surrounding the plethora of options available. This session initiates you into the whys & wherefores, architectural patterns, caveats and techniques that will augment your decision making process & boost your perception of architecting scalable, fault-tolerant & distributed solutions.
Summary of recent progress on Apache Drill, an open-source community-driven project to provide easy, dependable, fast and flexible ad hoc query capabilities.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
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.
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.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
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.
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.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
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.
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.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...
Non Relational Databases
1. § Focus
§ Raising awareness
§ Trends
§ High level
§ Questions
§ Why are non-relational databases increasing in usage?
§ What types or categories exist?
§ What are some examples in each category?
§ Why should I [the developer, the administrator, etc.] care?
A View of the Non-Relational Database Landscape
2. § Trend 1: Data is becoming more and more connected
§ Joins, joins, and more joins (relationships are exploding)
§ Trend 2: Data sets are becoming larger and larger
§ Instruments dump massive amounts of data in the lab
§ Trend 3: Data is becoming less and less structured
Why Are Non-Relational DBs Increasing In Usage?
3. § “Trend” 4: Cloud Computing
§ ..and perhaps more specifically, the scaling and fault tolerance needs.
§ For cloud providers, these are required hence addressed from the outset.
§ Backing up is replaced with having multiple active copies…
§ Data sets exist over multiple machines…
§ Nodes can crash and applications live to see another day…
§ Nodes can be added (or removed) at any point in time…
vs.
Why Are Non-Relational DBs Increasing In Usage?
4. § What is ACID?
§ A promise ring your RDBMS wears.
§ Atomic, Consistent, Isolated, Durable
§ ACID trips when:
§ Downtime is unacceptable
§ Reliability is >= 2 nodes
§ Challenging over networks
§ What is CAP Theorem?
§ Distributed systems can have two:
§ Consistency (data is correct all the time)
§ Availability (read and write all the time)
§ Partition Tolerance (plug and play nodes)
§ What is BASE?
§ More people much smarter than me came up with an ACID alternative:
§ Basically Available (appears to work all the time)
§ Soft state (doesn’t have to be consistent all the time…)
§ Eventually consistent (…but eventually it will be)
Turn Up The BASE
5. Key Value Databases Column-Oriented Databases
Stores entities as key value Stores entities by column
pairs in large hash tables (versus row)
Document Databases Graph Databases
Stores documents (JSON) Stores entities as nodes and edges
Distributed Databases
More attribute than type!
Non-Relational Database Landscape
6. Database System Type Open Source/Commercial/Proprietary
Dynamo Key Value Proprietary (Amazon)
SimpleDB Key Value Commercial (Amazon Web Services)
Project Voldemort Key Value Open Source (started @ LinkedIn)
Memcached Key Value Open Source
Redis Key Value Open Source
Tokyo Cabinet Key Value Open Source
Cassandra Column-oriented * Open Source (started @ Facebook)
BigTable Column-oriented * Proprietary (Google), Commercial (AppEngine)
Hypertable Column-oriented * Open Source (implementation of BigTable)
Hbase Column-oriented * Open Source (implementation of BigTable)
CouchDB Document Open Source
MongoDB Document Open Source
Neo4j Graph Open Source
Notable Non-Relational Databases
7. § Concepts
§ Domains: similar to table concept except schema-less.
§ Keys: arbitrary value.
§ Values: arbitrary blobs.
§ No explicit relationships between domains or within a domain.
§ Access
§ API (often SOAP or RESTful).
§ Some provide SQL-like syntax.
§ Basic filter predicates (=, !=, <, >, <=, >=). Ke Attributes
y
§ Integrity 1 Make: Nissan
§ Often contained in application code Model: Pathfinder
Color: Green
Year: 2003
2 Make: Nissan
Model: Pathfinder
Color: Green
Year: 2003
Transmission: Auto
Key Value Databases
8. § Memcached
§ Originally developed to speed up LiveJournal.com.
§ Generic in nature but intended for use in alleviating database load.
§ Lightening fast, distributed, RAM only, no persistence.
§ “Everyone” uses it: Facebook, Digg, Slashdot, Twitter, YouTube,
SourceForge, …
function get_foo(int userid)
{
result = db_select("SELECT * FROM users WHERE userid = ?", userid);
return result;
}
function get_foo(int userid)
{
result = memcached_fetch("userrow:" + userid);
if (!result) {
result = db_select("SELECT * FROM users WHERE userid = ?", userid);
memcached_add("userrow:" + userid, result);
}
return result;
}
Key Value Databases: Memcached
9. § SimpleDB
§ Written in Erlang (luckily you don’t need to know it to use it).
§ Eventually consistency is a key feature (concurrency!!)
§ Available via Amazon Web Services at very low cost.
§ Very common to use it in conjunction with other AWS offerings (EC2, S3,
SQS).
Key Value Databases: SimpleDB
11. § Overview
EmployeeID Name Position
1 Moe Director
2 Larry Developer
3 Curly Analyst
A gross (emphasis on gross) simplification of what this serializes too…
ROW: 1,Moe,Director;2,Larry,Developer;3,Curly,Analyst
COLUMN: 1,2,3;Moe,Larry,Curly;Director,Developer,Analyst
§ Where It Shines
§ Querying many rows for smaller subsets of data (not all columns)
§ Maximizes disk performance (read scans)
§ Where It Is Outperformed
§ Querying all columns of a single row
§ Writing a new row if all of the column data is supplied at the same time
Column Oriented Databases
12. § BigTable (and HBase, and Hypertable)
§ BigTable == Google
§ HBase == Interpretation of BigTable (Java) + Hadoop
§ Hypertable == Interpretation of BigTable (C++) + Hadoop
§ Collections of “Multi-dimensional Sparse Maps”
A–y cell => row, column, timestamp
A–n
A Contents B …
A’ B’ …
§ Rows § Columns
§ Name is an arbitrary string. § Two level naming structure
§ Ordered lexicographically. § family:optional_qualifier
§ Atomic access. § Families are a unit of access.
§ Creation is implicit. § Few column families in a table
§ Families can be marked with attributes.
§ Families can be assigned to locality groups
Column Like Databases: BigTable & Co.
14. § Overview
§ Similar to key value stores
§ Most employ JSON.
§ Inherently schema-less
§ Most are denormalized.
§ Often composed of collections (akin to tables w/o schema)
Document Databases
15. “… is a distributed, fault tolerant, and schema-free
document-oriented database accessible via a RESTful
HTTP/JSON API…”
§ Other Tidbits
§ Believe it or not, idea was inspired by Lotus Notes.
§ Hosted with Apache, written in Erlang.
§ Futon: clean, stream-lined administrator interface.
§ Basic API
§ Create: HTTP PUT
§ Read: HTTP GET
§ Update: HTTP POST
§ Delete: HTTP DELETE
§ Adding Structure To Semi-Structured Data
§ Views are the method of aggregating and reporting on documents.
§ Built on-demand, dynamically, and do affect underlying documents.
§ Views are persisted.
Document Databases: CouchDB
18. § Overview
§ Nodes represent entities.
§ Edges represent relationships.
§ Nodes and edges can have associated attributes (key values).
§ Most anything can be described as a graph.
§ Key value store with full support for relationships.
Graph Databases
19. § Overview
§ Open source.
§ Java based.
§ Lightweight (single <500k JAR with minimal dependencies).
§ Still very early in development but looks promising.
§ Can handle graphs of several billion nodes/relationships/properties.
§ Disk based, solid state drive (SSD) ready.
§ Optional layers to expose it as an RDF store (OWL, SPARQL).
§ Has RDBMS features (ACID, durable persistence)
Graph Databases: Neo4j
20. § If you’re in the cloud, you’re going to use them.
§ Amazon Web Services: SimpleDB
§ Google App Engine: BigTable
§ Open Source: Memcached, HBase, Hypertable, Cassandra, and more…
§ Break the habit; relational databases do not fit every problem.
§ Stuffing files into a RDBMS, maybe there’s something better?
§ Using a RDBMS for caching, perhaps a lighter-weight solution is better?
§ Cramming log data into a RDBMS, perhaps a key value store is better?
§ Despite the hype, relational databases are not doomed.
§ Though in my opinion their role and place will certainly change.
§ Scaling is a real challenge for relational databases.
§ Sharding is a band-aid, not feasible beyond a few nodes.
§ There is a hit in overcoming the initial learning curve
§ It changes how you build applications
Parting Thoughts & Musings