ArangoDB is a multi-model open source database that can be used as a document store, graph database, and key-value store using a single query language. It offers features like transactions, replication, sharding, and extensibility through JavaScript to provide a flexible database for various data models and use cases. The document presents ArangoDB as a database that can replace multiple specialized databases by providing multiple data models in a single system.
Domain Driven Design is a software development process that focuses on finding a common language for the involved parties. This language and the resulting models are taken from the domain rather than the technical details of the implementation. The goal is to improve the communication between customers, developers and all other involved groups. Even if Eric Evan's book about this topic was written almost ten years ago, this topic remains important because a lot of projects fail for communication reasons.
Relational databases have their own language and influence the design of software into a direction further away from the Domain: Entities have to be created for the sole purpose of adhering to best practices of relational database. Two kinds of NoSQL databases are changing that: Document stores and graph databases. In a document store you can model a "contains" relation in a more natural way and thereby express if this entity can exist outside of its surrounding entity. A graph database allows you to model relationships between entities in a straight forward way that can be expressed in the language of the domain.
In this talk I want to look at the way a multi model database that combines a document store and a graph database can help you to model your problems in a way that is understandable for all parties involved, and explain the benefits of this approach for the software development process.
In this talk I will explain the motivation behind the multi model database approach, discuss its advantages and limitations, and will keep the presentation concrete and practice oriented by showing concrete usage examples from node.js .
Recently a new breed of "multi-model" databases has emerged. They are a document store, a graph database and a key/value store combined in one program. Therefore they are able to cover a lot of use cases which otherwise would need multiple different database systems.
This approach promises a boost to the idea of "polyglot persistence", which has become very popular in recent years although it creates some friction in the form of data conversion and synchronisation between different systems. This is, because with a multi-model database one can enjoy the benefits of polyglot persistence without the disadvantages.
In this talk I will explain the motivation behind the multi-model approach, discuss its advantages and limitations, and will then risk to make some predictions about the NoSQL database market in five years time, which I shall only reveal during the talk.
Processing large-scale graphs with Google PregelMax Neunhöffer
Graphs are a very popular data structure to store relations like
friendship or web pages and their links. Therefore graph databases
have become popular recently and some of them even allow sharding,
i.e. automatic distribution of the data across multiple machines.
On the other hand, very computation-intensive algorithms for graphs are known and used in practice, and they often access very large data sets, which leads to heavy communication loads.
Therefore, it is an obvious idea to run such graph algorithms on the database servers, close to the data, making use of the computational power of the storage nodes.
Google's Pregel framework allows to implement a lot of graph algorithms in a general system and plays a role similar to the map-reduce skeleton, but for graphs.
In this talk I will explain the framework and describe its implementation in the multi-model database ArangoDB.
In this talk we present the term polyglot persistence, give a brief introduction to the world of NoSQL database and point out the benefits and costs of polyglot persistence. Thereafter we present the idea of a multi-model database that reduces the costs for polyglot persistence but keeps its benefits. Next up we present ArangoDB as a Multi-Model database
Jan Steemann: Modelling data in a schema free world (Talk held at Froscon, 2...ArangoDB Database
Even though most NoSQL databases follow
the "schemafree" data paradigma, it is still import to choose the right data model to make the best of the underlying database technology. This talk provides an overview of
the different data storage models available in popular NoSQL databases. It also introduces some best practices on how to model your data for both best performance and best querying.
Here is my seminar presentation on No-SQL Databases. it includes all the types of nosql databases, merits & demerits of nosql databases, examples of nosql databases etc.
For seminar report of NoSQL Databases please contact me: ndc@live.in
Domain Driven Design is a software development process that focuses on finding a common language for the involved parties. This language and the resulting models are taken from the domain rather than the technical details of the implementation. The goal is to improve the communication between customers, developers and all other involved groups. Even if Eric Evan's book about this topic was written almost ten years ago, this topic remains important because a lot of projects fail for communication reasons.
Relational databases have their own language and influence the design of software into a direction further away from the Domain: Entities have to be created for the sole purpose of adhering to best practices of relational database. Two kinds of NoSQL databases are changing that: Document stores and graph databases. In a document store you can model a "contains" relation in a more natural way and thereby express if this entity can exist outside of its surrounding entity. A graph database allows you to model relationships between entities in a straight forward way that can be expressed in the language of the domain.
In this talk I want to look at the way a multi model database that combines a document store and a graph database can help you to model your problems in a way that is understandable for all parties involved, and explain the benefits of this approach for the software development process.
In this talk I will explain the motivation behind the multi model database approach, discuss its advantages and limitations, and will keep the presentation concrete and practice oriented by showing concrete usage examples from node.js .
Recently a new breed of "multi-model" databases has emerged. They are a document store, a graph database and a key/value store combined in one program. Therefore they are able to cover a lot of use cases which otherwise would need multiple different database systems.
This approach promises a boost to the idea of "polyglot persistence", which has become very popular in recent years although it creates some friction in the form of data conversion and synchronisation between different systems. This is, because with a multi-model database one can enjoy the benefits of polyglot persistence without the disadvantages.
In this talk I will explain the motivation behind the multi-model approach, discuss its advantages and limitations, and will then risk to make some predictions about the NoSQL database market in five years time, which I shall only reveal during the talk.
Processing large-scale graphs with Google PregelMax Neunhöffer
Graphs are a very popular data structure to store relations like
friendship or web pages and their links. Therefore graph databases
have become popular recently and some of them even allow sharding,
i.e. automatic distribution of the data across multiple machines.
On the other hand, very computation-intensive algorithms for graphs are known and used in practice, and they often access very large data sets, which leads to heavy communication loads.
Therefore, it is an obvious idea to run such graph algorithms on the database servers, close to the data, making use of the computational power of the storage nodes.
Google's Pregel framework allows to implement a lot of graph algorithms in a general system and plays a role similar to the map-reduce skeleton, but for graphs.
In this talk I will explain the framework and describe its implementation in the multi-model database ArangoDB.
In this talk we present the term polyglot persistence, give a brief introduction to the world of NoSQL database and point out the benefits and costs of polyglot persistence. Thereafter we present the idea of a multi-model database that reduces the costs for polyglot persistence but keeps its benefits. Next up we present ArangoDB as a Multi-Model database
Jan Steemann: Modelling data in a schema free world (Talk held at Froscon, 2...ArangoDB Database
Even though most NoSQL databases follow
the "schemafree" data paradigma, it is still import to choose the right data model to make the best of the underlying database technology. This talk provides an overview of
the different data storage models available in popular NoSQL databases. It also introduces some best practices on how to model your data for both best performance and best querying.
Here is my seminar presentation on No-SQL Databases. it includes all the types of nosql databases, merits & demerits of nosql databases, examples of nosql databases etc.
For seminar report of NoSQL Databases please contact me: ndc@live.in
158ltd.com gives a rapid introduction to NoSQL databases: where they came from, the nature of the data models they use, and the different way you have to think about consistency.
FOXX - a Javascript application framework on top of ArangoDBArangoDB Database
Foxx allows you to build APIs directly on top of the database ArangoDB in Javascript and therefore skip the middleman (Rails, Django, Symfony or whatever your favorite web framework is). Foxx is designed with simplicity and the specific use case of modern client-side MVC frameworks in mind.
In 2014 we had to do a major overhaul of ArangoDB's database engine,because we wanted to introduce a write-ahead log. Since for a database this change is similar in nature to the proverbial open-heart surgery for humans, it was clear from day one that this would be a difficult endeavour with a lot of risk to break things. Rather fundamental changes were needed in nearly all places of the kernel code and it seemedimpossible to serialise the work to keep the system in a working state. As usual, time was at a premium, since the next major release had to go out of the door in 2 months time.
In this talk I will tell the story of this overhaul, explain the role of unit tests and continuous integration and describe the challenges we faced and how finally overcame them.
guacamole: an Object Document Mapper for ArangoDBMax Neunhöffer
In this talk I will give a brief introduction and overview for guacamole, showing how easy it is to get started with using ArangoDB as the persistence layer for a Rails app. I will also explain the philosophy behind ArangoDB's "multi-model approach", but still show concrete code examples, and all of this in 15 minutes.
GraphTech Ecosystem - part 1: Graph DatabasesLinkurious
The graph ecosystem presentation lists and introduces a vast majority of storage systems for graph-like data: native graph databases, RDF databases, multi-model systems or systems with a graph API.
This presentation explains why NoSQL databases came over SQL databases although SQL databases has been successfully technology for more than twenty years. Moreover, This presentation discuses the characteristics and classifications of NoSQL databases. Finally, These slides cover four NoSQL databases briefly.
As more businesses realised that data, in all forms and sizes, is critical to making the best possible decisions, we see the continued growth of systems that support massive volume of non-relational or unstructured forms of data. Nothing shows the picture more starkly than the Gartner Magic quadrant for operational database management systems, which assumes that, by 2017, all leading operational DBMSs will offer multiple data models, relational and NoSQL, in a single DBMS platform. Having a single data platform for managing both well-structured data and NoSQL data is beneficial to users; this approach reduces significantly integration, migration, development, maintenance, and operational issues. Therefore, a challenging research work is how to develop efficient consolidated single data management platform covering both relational data and NoSQL to reduce integration issues, simplify operations, and eliminate migration issues.
In this tutorial, we review the previous work on multi-model data management and provide the insights on the research challenges and directions for future work.
Papers and more materials on this tutorial can be found at: http://udbms.cs.helsinki.fi/?tutorials
We will take a deep dive into ArangoDB (https://www.arangodb.com/) together with Max (https://www.linkedin.com/in/maxneunhoeffer) one of the core developers of the product.
ArangoDB is a multi-model database, which means that it is a document store, a key/value store and a graph database, all in one engine and with a query language that supports all three data models, as well as joins and transactions. Queries can use a single data model or can even mix them.
ArangoDB scales out horizontally with convenient cluster deployment using Apache Mesos. Furthermore, the HTTP API can easily be extended by server-side JavaScript code using high performance access to the C++ database core.
During the talk I will show all these features using several different cloud deployments, since in most projects one will not deploy a ArangoDB monolith, but rather multiple instances, each either a possibly replicated single server, or a cluster. This demonstrates that all these properties together make ArangoDB a very useful and valuable tool in modern microservice oriented architectures.
158ltd.com gives a rapid introduction to NoSQL databases: where they came from, the nature of the data models they use, and the different way you have to think about consistency.
FOXX - a Javascript application framework on top of ArangoDBArangoDB Database
Foxx allows you to build APIs directly on top of the database ArangoDB in Javascript and therefore skip the middleman (Rails, Django, Symfony or whatever your favorite web framework is). Foxx is designed with simplicity and the specific use case of modern client-side MVC frameworks in mind.
In 2014 we had to do a major overhaul of ArangoDB's database engine,because we wanted to introduce a write-ahead log. Since for a database this change is similar in nature to the proverbial open-heart surgery for humans, it was clear from day one that this would be a difficult endeavour with a lot of risk to break things. Rather fundamental changes were needed in nearly all places of the kernel code and it seemedimpossible to serialise the work to keep the system in a working state. As usual, time was at a premium, since the next major release had to go out of the door in 2 months time.
In this talk I will tell the story of this overhaul, explain the role of unit tests and continuous integration and describe the challenges we faced and how finally overcame them.
guacamole: an Object Document Mapper for ArangoDBMax Neunhöffer
In this talk I will give a brief introduction and overview for guacamole, showing how easy it is to get started with using ArangoDB as the persistence layer for a Rails app. I will also explain the philosophy behind ArangoDB's "multi-model approach", but still show concrete code examples, and all of this in 15 minutes.
GraphTech Ecosystem - part 1: Graph DatabasesLinkurious
The graph ecosystem presentation lists and introduces a vast majority of storage systems for graph-like data: native graph databases, RDF databases, multi-model systems or systems with a graph API.
This presentation explains why NoSQL databases came over SQL databases although SQL databases has been successfully technology for more than twenty years. Moreover, This presentation discuses the characteristics and classifications of NoSQL databases. Finally, These slides cover four NoSQL databases briefly.
As more businesses realised that data, in all forms and sizes, is critical to making the best possible decisions, we see the continued growth of systems that support massive volume of non-relational or unstructured forms of data. Nothing shows the picture more starkly than the Gartner Magic quadrant for operational database management systems, which assumes that, by 2017, all leading operational DBMSs will offer multiple data models, relational and NoSQL, in a single DBMS platform. Having a single data platform for managing both well-structured data and NoSQL data is beneficial to users; this approach reduces significantly integration, migration, development, maintenance, and operational issues. Therefore, a challenging research work is how to develop efficient consolidated single data management platform covering both relational data and NoSQL to reduce integration issues, simplify operations, and eliminate migration issues.
In this tutorial, we review the previous work on multi-model data management and provide the insights on the research challenges and directions for future work.
Papers and more materials on this tutorial can be found at: http://udbms.cs.helsinki.fi/?tutorials
We will take a deep dive into ArangoDB (https://www.arangodb.com/) together with Max (https://www.linkedin.com/in/maxneunhoeffer) one of the core developers of the product.
ArangoDB is a multi-model database, which means that it is a document store, a key/value store and a graph database, all in one engine and with a query language that supports all three data models, as well as joins and transactions. Queries can use a single data model or can even mix them.
ArangoDB scales out horizontally with convenient cluster deployment using Apache Mesos. Furthermore, the HTTP API can easily be extended by server-side JavaScript code using high performance access to the C++ database core.
During the talk I will show all these features using several different cloud deployments, since in most projects one will not deploy a ArangoDB monolith, but rather multiple instances, each either a possibly replicated single server, or a cluster. This demonstrates that all these properties together make ArangoDB a very useful and valuable tool in modern microservice oriented architectures.
3.Implementation with NOSQL databases Document Databases (Mongodb).pptxRushikeshChikane2
this Chapter gives information about Document Based Database and Graph based Database. It gives their basic structures, Features,applications ,Limitations and use cases
As technology and needs evolve and the need for scalable and high availability solutions increase there is a need to evaluate new databases. The lack of clarity in the market makes in difficult for IT stakeholders to understand the differences between the solutions available and the choice to make. The key areas to consider while evaluating NoSql databases are data model, query model, consistency model, APIs, support and community strength.
Comparative study of no sql document, column store databases and evaluation o...ijdms
In the last decade, rapid growth in mobile applications, web technologies, social media generating
unstructured data has led to the advent of various nosql data stores. Demands of web scale are in
increasing trend everyday and nosql databases are evolving to meet up with stern big data requirements.
The purpose of this paper is to explore nosql technologies and present a comparative study of document
and column store nosql databases such as cassandra, MongoDB and Hbase in various attributes of
relational and distributed database system principles. Detailed study and analysis of architecture and
internal working cassandra, Mongo DB and HBase is done theoretically and core concepts are depicted.
This paper also presents evaluation of cassandra for an industry specific use case and results are
published.
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.
Recently, ArangoDB integrated its cluster management with Apache Mesos. This makes it now possible to launch an ArangoDB cluster on a Mesos cluster with a single, albeit complex shell command. In a DCOS-enabled Mesosphere cluster this is even easier, because one can use the dcos subcommand for ArangoDB, which essentially turns a Mesosphere cluster into a single, large computer.
In this talk I explain the whole setup and show (live on stage) how to deploy ArangoDB clusters on Amazon Web Services, and how we used this to scale ArangoDB up until it could sustain 1000000 document writes per second.
Recently, ArangoDB integrated its cluster management with Apache Mesos. This makes it now possible to launch an ArangoDB cluster on a Mesos cluster with a single, albeit complex shell command. In a DCOS-enabled Mesosphere cluster this is even easier, because one can use the dcos subcommand for ArangoDB, which essentially turns a Mesosphere cluster into a single, large computer.
In this talk I explain the whole setup and show (live on stage) how to deploy ArangoDB clusters on Google Compute Engine, and how we used this to scale ArangoDB up until it could sustain 1000000 document writes per second.
Backbone using Extensible Database APIs over HTTPMax Neunhöffer
These days, more and more software applications are designed using a micro services architecture, that is, as suites of independently deployable services, talking to each other with well-defined interfaces. This approach is helped by the fact that many NoSQL databases expose their API through HTTP, which makes it particularly easy to define the interfaces.
The multi-model NoSQL database ArangoDB embeds Google's V8 JavaScript engine and features the Foxx framework, which allows the developer to extend ArangoDB's API by user defined JavaScript code that runs on the database server.
In this talk I will explain the benefits of this approach to the software architecture and development process. I will keep the presentation practice oriented by showing concrete examples in ArangoDB and JavaScript, using Backbone.js
Complex queries in a distributed multi-model databaseMax Neunhöffer
A multi-model database is a document store, a graph database as well as a key/value store. To allow for convenient and powerful querying such a database needs a query language that understands all three data models and allows to mix these models in queries. For example, it should be possible to find some documents in a collection according to some criteria, then follow some edges in a graph in which the documents represent vertices, and finally join the results with documents from yet another collection.
In this talk I will explain how a query engine for such a language works, give an overview of the life of a query from parsing, over translation into an execution plan, the optimisation phase and finally the execution. I will show how distributed query execution plans look like, how the query optimiser reasons about them and how the distributed execution works.
ArangoDB is an open source, multi-model NoSQL database that is written in C++ and embeds Google's V8 engine to implement the higher levels of its functionality in JavaScript. Recently we decided to switch from C++03 to C++11 for the database kernel. In this talk I will first give a short overview of the software architecture of ArangoDB and proceed to tell you about our practical experiences with the switch to C++11. I will explain which of the parts of the "new" standard have been more important and which have been less useful, and I will report about the difficulties we encountered.
Extensible Database APIs and their role in Software ArchitectureMax Neunhöffer
This event will start with a presentation on “Extensible database APIs and their role in software architecture”, centered around JavaScript. This will be followed by a hands-on interactive workshop. Participants with their own computers will learn how to create a small web application with a database backend, within the session, using only JavaScript. This will be a guided hands-on session using the multi-model NoSQL database ArangoDB and its Foxx JavaScript extension framework. Presenting this workshop will be Max Neunhöffer from https://www.arangodb.com/.
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Developing Distributed High-performance Computing Capabilities of an Open Sci...
Oslo bekk2014
1. ArangoDB — Is Multi-Model
the Future of NoSQL?
Oslo, 23 October 2014
Max Neunhöffer
www.arangodb.com
2. Max Neunhöffer
I am a mathematician
“Earlier life”: Research in Computer Algebra
(Computational Group Theory)
Always juggled with big data
Now: working in database development, NoSQL, ArangoDB
I like:
research,
hacking,
teaching,
tickling the highest performance out of computer systems.
1
3. ArangoDB GmbH
triAGENS GmbH offers consulting services since 2004:
software architecture
project management
software development
business analysis
a lot of experience with specialised database systems.
have done NoSQL, before the term was coined at all
2011/2012, an idea emerged:
to build the database one had wished to have all those years!
development of ArangoDB as open source software since 2012
ArangoDB GmbH: spin-off to take care of ArangoDB (2014)
2
4. Polyglot Persistence
Idea
Use the right data model for each part of a system.
For an application, persist
an object or structured data as a JSON document,
a hash table in a key/value store,
relations between objects in a graph database,
a homogeneous array in a relational DBMS.
If the table has many empty cells or inhomogeneous rows, use
a column-based database.
Take scalability needs into account!
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5. Document and key/value stores
Document store
A document store stores a set of documents, which usually
means JSON data, these sets are called collections. The
database has access to the contents of the documents.
each document in the collection has a unique key
secondary indexes possible, leading to more powerful queries
different documents in the same collection: structure can vary
no schema is required for a collection
database normalisation can be relaxed
“Special case”: key/value store
Opaque values, restrict to key lookup without secondary
indexes:
=) high performance and perfect scalability
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6. Graph databases
Graph database
A graph database stores a labelled graph. Vertices and
edges can be documents. Graphs are good to model
relations.
graphs often describe data very naturally (e.g. the facebook
friendship graph)
graphs can be stored using tables, however, graph queries
notoriously lead to expensive joins
there are interesting and useful graph algorithms like “shortest
path” or “neighbourhood”
need a good query language to reap the bene1ts
horizontal scalability is troublesome
graph databases vary widely in scope and usage, no standard
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7. A typical Use Case — an Online Shop
We need to hold
customer data: usually homogeneous, but still variations
=) use a document store:
product data: even for a specialised business quite
inhomogeneous
=) use a document store:
shopping carts: need very fast lookup by session key
=) use a key/value store:
order and sales data: relate customers and products
=) use a document store:
recommendation engine data: links between different entities
=) use a graph database:
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8. Polyglot Persistence is nice, but . . .
Consequence: One needs multiple database systems in the persis-tence
layer of a single project!
Polyglot persistence introduces some friction through
data synchronisation,
data conversion,
increased installation and administration effort,
more training needs.
Wouldn’t it be nice, . . .
. . . to enjoy the bene1ts without paying with the
disadvantages?
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9. The Multi-Model Approach
Multi-model database
A Multi-model database combines a document store with a
graph database and is at the same time a key/value store.
Vertices are documents in a vertex collection,
edges are documents in an edge collection.
a single, common query language for all three data models
is able to compete with specialised products on their turf
allows for polyglot persistence using a single database
queries can mix the different data models
can replace a RDMBS in many cases
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10. A Map of the NoSQL Landscape
Transaction Processing DBs
Map/reduce
Column Stores
Analytic processing DBs
Extensibility
Complex queries
Documents
Massively distributed
Graphs
Structured
Data
Key/Value
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11. is a multi-model database (document store & graph database),
is open source and free (Apache 2 license),
offers convenient queries (via HTTP/REST and AQL),
memory eZcient by shape detection,
uses JavaScript throughout (Google’s V8 built into server),
API extensible by JavaScript code in the Foxx framework,
offers many drivers for a wide range of languages,
is easy to use with web front end and good documentation,
enjoys good professional as well as community support
and has sharding since Version 2.0.
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12. A Map of the NoSQL Landscape
Transaction Processing DBs
Map/reduce
Column Stores
Analytic processing DBs
Extensibility
Complex queries
Documents
Massively distributed
Graphs
Structured
Data
Key/Value
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14. Strong Consistency
ArangoDB offers
atomic and isolated CRUD operations for single documents,
transactions spanning multiple documents and multiple
collections,
snapshot semantics for complex queries,
very secure durable storage using append only and storing
multiple revisions,
all this for documents as well as for graphs.
In the (not too distant) future, ArangoDB will
offer the same ACID semantics even with sharding,
implement complete MVCC semantics to allow for lock-free
concurrent transactions.
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15. Replication and Sharding — horizontal scalability
Right now, ArangoDB provides
easy setup of (asynchronous) replication,
which allows read access parallelisation (master/slaves setup),
sharding with automatic data distribution to multiple servers.
Very soon, ArangoDB will feature
fault tolerance by automatic failover and synchronous
replication in cluster mode,
zero administration by a self-reparing and self-balancing
cluster architecture.
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16. Powerful query language: AQL
The built in Arango Query Language AQL allows
complex, powerful and convenient queries,
with transaction semantics,
allowing to do joins,
with user de1nable functions (in JavaScript).
AQL is independent of the driver used and
offers protection against injections by design.
For Version 2.3, we are reengineering the AQL query engine:
use a C++ implementation for high performance,
optimise distributed queries in the cluster.
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17. Extensible through JavaScript and Foxx
The HTTP API of ArangoDB
can be extended by user-de1ned JavaScript code,
that is executed in the DB server for high performance.
This is formalised by the Foxx framework,
which allows to implement complex, user-de1ned APIs with
direct access to the DB engine.
Very 2exible and secure authentication schemes can be
implemented conveniently by the user in JavaScript.
Because JavaScript runs everywhere (in the DB server as well
as in the browser), one can use the same libraries in the
back-end and in the front-end.
=) implement your own micro services
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