This document provides information about the topic of NoSQL non-relational databases. It begins with an introduction to the increasing volume of data being generated and the need for storage and analysis systems that can handle large amounts of data at high speeds. It then provides overviews of different types of NoSQL databases, including document-oriented databases, key-value stores, graph databases, and column-oriented databases. For each type, it discusses what they are, popular examples, advantages and disadvantages. The document aims to educate about NoSQL databases as an alternative to traditional relational databases for large-scale data needs.
The document provides an overview of NoSQL and MongoDB. It discusses that NoSQL databases were built for large datasets and cloud applications. It covers some of the main types of NoSQL databases like document stores, key-value stores, and column family stores. The document also compares NoSQL to SQL/relational databases, discussing how NoSQL is more flexible and scales horizontally. MongoDB is presented as a popular document-oriented NoSQL database, covering its flexible schema, horizontal scaling, and replication features.
Is emergence of NoSQL killed RDBMS and SQL? This slide discusses what is NoSQL and it's history. This also discusses briefly about polyglot persistence.
1) NoSQL databases were developed to address problems with scaling relational databases (RDBMS) and fitting certain types of data and use cases.
2) NoSQL databases are non-relational and come in different types including key-value, wide column, document, and graph databases. They are designed for high scale, simplicity, and distribution across clusters.
3) The cloud allows for massive data analysis by providing unlimited scalability through mounting large compute clusters to process vast amounts of diverse data from various sources.
What Your Database Query is Really DoingDave Stokes
Do you ever wonder what your database servers is REALLY doing with that query you just wrote. This is a high level overview of the process of running a query
This document compares SQL and NoSQL databases. It defines databases, describes different types including relational and NoSQL, and explains key differences between SQL and NoSQL in areas like scaling, modeling, and query syntax. SQL databases are better suited for projects with logical related discrete data requirements and data integrity needs, while NoSQL is more ideal for projects with unrelated, evolving data where speed and scalability are important. MongoDB is provided as an example of a NoSQL database, and the CAP theorem is introduced to explain tradeoffs in distributed systems.
The document provides an overview of NoSQL and MongoDB. It discusses that NoSQL databases were built for large datasets and cloud applications. It covers some of the main types of NoSQL databases like document stores, key-value stores, and column family stores. The document also compares NoSQL to SQL/relational databases, discussing how NoSQL is more flexible and scales horizontally. MongoDB is presented as a popular document-oriented NoSQL database, covering its flexible schema, horizontal scaling, and replication features.
Is emergence of NoSQL killed RDBMS and SQL? This slide discusses what is NoSQL and it's history. This also discusses briefly about polyglot persistence.
1) NoSQL databases were developed to address problems with scaling relational databases (RDBMS) and fitting certain types of data and use cases.
2) NoSQL databases are non-relational and come in different types including key-value, wide column, document, and graph databases. They are designed for high scale, simplicity, and distribution across clusters.
3) The cloud allows for massive data analysis by providing unlimited scalability through mounting large compute clusters to process vast amounts of diverse data from various sources.
What Your Database Query is Really DoingDave Stokes
Do you ever wonder what your database servers is REALLY doing with that query you just wrote. This is a high level overview of the process of running a query
This document compares SQL and NoSQL databases. It defines databases, describes different types including relational and NoSQL, and explains key differences between SQL and NoSQL in areas like scaling, modeling, and query syntax. SQL databases are better suited for projects with logical related discrete data requirements and data integrity needs, while NoSQL is more ideal for projects with unrelated, evolving data where speed and scalability are important. MongoDB is provided as an example of a NoSQL database, and the CAP theorem is introduced to explain tradeoffs in distributed systems.
Lessons learnt coverting from SQL to NoSQLEnda Farrell
The document summarizes lessons learned from migrating a large, highly relational SQL database with tens of millions of records across 32 tables to a "classic" NoSQL key-value store. Some key challenges included running the SQL and NoSQL databases in parallel during migration, reconciling differences between the data stores, and addressing more limited querying capabilities of NoSQL. It emphasizes planning for people impacts and tooling needs like data migration utilities and improved testing. Overall, the migration increased flexibility but also introduced complexity, so thorough planning and monitoring were important lessons.
The databases SQL and NoSQL have their own importance, and it profoundly depends on your business requirement and objectives. One of the biggest factors in understanding which database is the better choice depends on the type of data that needs to be stored. To Know more visit at https://www.zenesys.com/blog/sql-vs-nosql-top-10-comparisons
This document provides an overview of NoSQL databases. It discusses that NoSQL databases offer more flexibility, higher performance, scalability, and choices compared to relational databases. The four main types of NoSQL databases are column family stores, key-value stores, document stores, and graph stores. Each has their own advantages and disadvantages for storing and querying data.
Enterprise NoSQL: Silver Bullet or Poison PillBilly Newport
Enterprise NoSQL Silver bullet or poison pill? discusses the pros and cons of NoSQL databases compared to SQL databases. While SQL databases will remain prevalent, NoSQL databases offer alternative data storage options with different tradeoffs. NoSQL systems typically relax constraints of SQL like schema rigidity in exchange for implementation flexibility, but this comes at the cost of features like joins and global indexes. NoSQL also shifts the system of record away from a single database, requiring applications to handle consistency and creating multiple copies of data to scale.
This document provides an overview of non-relational (NoSQL) databases. It discusses the history and characteristics of NoSQL databases, including that they do not require rigid schemas and can automatically scale across servers. The document also categorizes major types of NoSQL databases, describes some popular NoSQL databases like Dynamo and Cassandra, and discusses benefits and limitations of both SQL and NoSQL databases.
Key bank saved $500,000 using data mining from their customer database. Airlines use data analysis to optimize pricing on each flight. Progressive Insurance offers usage-based insurance plans using customer data. Data becomes the basis for strategic, tactical, and operational decision making. Relational databases store structured data efficiently while dimensional databases retrieve data efficiently through aggregation. Data warehouses implement dimensional modeling through data cubes to enable online analytical processing.
The document discusses NoSQL databases, including what NoSQL is, various data models like key-value, document, column-family and graph databases. It describes types of NoSQL databases and examples. Reasons for using NoSQL databases are provided, such as their ability to handle schema migrations easily, support multiple data formats, avoid impedance mismatch and automatically shard data across servers.
SQL For Programmers -- Boston Big Data Techcon April 27thDave Stokes
SQL For Programmers is an introduction to SQL concepts, when SQL is a better choice, and a look at the future of databases. Presented April 27th, 2015 at Big Data Techcon Boston
NoSQL and NewSQL: Tradeoffs between Scalable Performance & ConsistencyScyllaDB
This webinar compares NoSQL and NewSQL databases. We will look at the significant architectural differences between the two, tradeoffs between availability, scalable performance and consistency, data models, and share benchmark results to display the performance implications of NoSQL versus NewSQL.
Couchbase Data Platform | Big Data DemystifiedOmid Vahdaty
Couchbase is a popular open source NoSQL platform used by giants like Apple, LinkedIn, Walmart, Visa and many others and runs on-premise or in a public/hybrid/multi cloud.
Couchbase has a sub-millisecond K/V cache integrated with a document based DB, a unique and many more services and features.
In this session we will talk about the unique architecture of Couchbase, its unique N1QL language - a SQL-Like language that is ANSI compliant, the services and features Couchbase offers and demonstrate some of them live.
We will also discuss what makes Couchbase different than other popular NoSQL platforms like MongoDB, Cassandra, Redis, DynamoDB etc.
At the end we will talk about the next version of Couchbase (6.5) that will be released later this year and about Couchbase 7.0 that will be released next year.
The document discusses modern databases and NoSQL databases. It defines requirements for a modern database as scaling, adapting to change, and unleashing data. It then discusses uses of modern databases in real-time applications. New types of data from the web, mobile, and IoT require flexibility that relational databases cannot provide, leading to interest in NoSQL databases. The document outlines the history of NoSQL and describes key-value, document, column, and graph database types. It compares NoSQL to relational databases and discusses how different companies use NoSQL.
The document provides an overview of NoSQL databases, including:
- NoSQL databases are non-tabular and can handle big data and real-time applications better than SQL databases through horizontal scaling and flexibility.
- The main types of NoSQL databases are document stores, key-value stores, column-family stores, and graph databases.
- Cassandra is introduced as an example of a column-family store database, with a focus on its data model and use for clients.
This document presents an introduction to NoSQL databases. It begins with an overview comparing SQL and NoSQL databases, describing the architecture of NoSQL databases. Examples of different types of NoSQL databases are provided, including key-value stores, column family stores, document databases and graph databases. MapReduce programming is also introduced. Popular NoSQL databases like Cassandra, MongoDB, HBase, and CouchDB are described. The document concludes that NoSQL is well-suited for large, highly distributed data problems.
The document compares NoSQL and SQL databases. It notes that NoSQL databases are non-relational and have dynamic schemas that can accommodate unstructured data, while SQL databases are relational and have strict, predefined schemas. NoSQL databases offer more flexibility in data structure, but SQL databases provide better support for transactions and data integrity. The document also discusses differences in queries, scaling, and consistency between the two database types.
One Database Countless Possibilities for Mission-critical ApplicationsFairCom
This presentation was given during FairCom's 2016 Data Strategies Roadshow to Austin, New York City, and Salt Lake City by Evaldo Horn De Oliveira.
Database technology is difficult to predict, yet in 2016 the crossroads of SQL or NoSQL becomes more evident in many cases. This deck talks about not making a choice between one method or another, but finding a way to blend relational and non relational data within the same database.
c-treeACE V11 was announced in November 2015, and gives software developers a strong ability to build applications to use the speed of non-relational data, but have access to analyze data through SQL.
You can learn more about c-treeACE V11 at http://www.faircom.com/v11-is-here
The presentation provides an overview of NoSQL databases, including a brief history of databases, the characteristics of NoSQL databases, different data models like key-value, document, column family and graph databases. It discusses why NoSQL databases were developed as relational databases do not scale well for distributed applications. The CAP theorem is also explained, which states that only two out of consistency, availability and partition tolerance can be achieved in a distributed system.
This document provides an introduction to NoSQL databases. It begins by explaining what a database management system (DBMS) and relational database management system (RDBMS) are. It then discusses some limitations of relational databases and how NoSQL databases address those limitations by being non-relational, schema-free, and offering simple APIs. The document provides a brief history of NoSQL databases and defines what NoSQL is and why it was developed to handle large, growing amounts of unstructured data from sources like social networks. It outlines some key features of NoSQL databases.
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
Lessons learnt coverting from SQL to NoSQLEnda Farrell
The document summarizes lessons learned from migrating a large, highly relational SQL database with tens of millions of records across 32 tables to a "classic" NoSQL key-value store. Some key challenges included running the SQL and NoSQL databases in parallel during migration, reconciling differences between the data stores, and addressing more limited querying capabilities of NoSQL. It emphasizes planning for people impacts and tooling needs like data migration utilities and improved testing. Overall, the migration increased flexibility but also introduced complexity, so thorough planning and monitoring were important lessons.
The databases SQL and NoSQL have their own importance, and it profoundly depends on your business requirement and objectives. One of the biggest factors in understanding which database is the better choice depends on the type of data that needs to be stored. To Know more visit at https://www.zenesys.com/blog/sql-vs-nosql-top-10-comparisons
This document provides an overview of NoSQL databases. It discusses that NoSQL databases offer more flexibility, higher performance, scalability, and choices compared to relational databases. The four main types of NoSQL databases are column family stores, key-value stores, document stores, and graph stores. Each has their own advantages and disadvantages for storing and querying data.
Enterprise NoSQL: Silver Bullet or Poison PillBilly Newport
Enterprise NoSQL Silver bullet or poison pill? discusses the pros and cons of NoSQL databases compared to SQL databases. While SQL databases will remain prevalent, NoSQL databases offer alternative data storage options with different tradeoffs. NoSQL systems typically relax constraints of SQL like schema rigidity in exchange for implementation flexibility, but this comes at the cost of features like joins and global indexes. NoSQL also shifts the system of record away from a single database, requiring applications to handle consistency and creating multiple copies of data to scale.
This document provides an overview of non-relational (NoSQL) databases. It discusses the history and characteristics of NoSQL databases, including that they do not require rigid schemas and can automatically scale across servers. The document also categorizes major types of NoSQL databases, describes some popular NoSQL databases like Dynamo and Cassandra, and discusses benefits and limitations of both SQL and NoSQL databases.
Key bank saved $500,000 using data mining from their customer database. Airlines use data analysis to optimize pricing on each flight. Progressive Insurance offers usage-based insurance plans using customer data. Data becomes the basis for strategic, tactical, and operational decision making. Relational databases store structured data efficiently while dimensional databases retrieve data efficiently through aggregation. Data warehouses implement dimensional modeling through data cubes to enable online analytical processing.
The document discusses NoSQL databases, including what NoSQL is, various data models like key-value, document, column-family and graph databases. It describes types of NoSQL databases and examples. Reasons for using NoSQL databases are provided, such as their ability to handle schema migrations easily, support multiple data formats, avoid impedance mismatch and automatically shard data across servers.
SQL For Programmers -- Boston Big Data Techcon April 27thDave Stokes
SQL For Programmers is an introduction to SQL concepts, when SQL is a better choice, and a look at the future of databases. Presented April 27th, 2015 at Big Data Techcon Boston
NoSQL and NewSQL: Tradeoffs between Scalable Performance & ConsistencyScyllaDB
This webinar compares NoSQL and NewSQL databases. We will look at the significant architectural differences between the two, tradeoffs between availability, scalable performance and consistency, data models, and share benchmark results to display the performance implications of NoSQL versus NewSQL.
Couchbase Data Platform | Big Data DemystifiedOmid Vahdaty
Couchbase is a popular open source NoSQL platform used by giants like Apple, LinkedIn, Walmart, Visa and many others and runs on-premise or in a public/hybrid/multi cloud.
Couchbase has a sub-millisecond K/V cache integrated with a document based DB, a unique and many more services and features.
In this session we will talk about the unique architecture of Couchbase, its unique N1QL language - a SQL-Like language that is ANSI compliant, the services and features Couchbase offers and demonstrate some of them live.
We will also discuss what makes Couchbase different than other popular NoSQL platforms like MongoDB, Cassandra, Redis, DynamoDB etc.
At the end we will talk about the next version of Couchbase (6.5) that will be released later this year and about Couchbase 7.0 that will be released next year.
The document discusses modern databases and NoSQL databases. It defines requirements for a modern database as scaling, adapting to change, and unleashing data. It then discusses uses of modern databases in real-time applications. New types of data from the web, mobile, and IoT require flexibility that relational databases cannot provide, leading to interest in NoSQL databases. The document outlines the history of NoSQL and describes key-value, document, column, and graph database types. It compares NoSQL to relational databases and discusses how different companies use NoSQL.
The document provides an overview of NoSQL databases, including:
- NoSQL databases are non-tabular and can handle big data and real-time applications better than SQL databases through horizontal scaling and flexibility.
- The main types of NoSQL databases are document stores, key-value stores, column-family stores, and graph databases.
- Cassandra is introduced as an example of a column-family store database, with a focus on its data model and use for clients.
This document presents an introduction to NoSQL databases. It begins with an overview comparing SQL and NoSQL databases, describing the architecture of NoSQL databases. Examples of different types of NoSQL databases are provided, including key-value stores, column family stores, document databases and graph databases. MapReduce programming is also introduced. Popular NoSQL databases like Cassandra, MongoDB, HBase, and CouchDB are described. The document concludes that NoSQL is well-suited for large, highly distributed data problems.
The document compares NoSQL and SQL databases. It notes that NoSQL databases are non-relational and have dynamic schemas that can accommodate unstructured data, while SQL databases are relational and have strict, predefined schemas. NoSQL databases offer more flexibility in data structure, but SQL databases provide better support for transactions and data integrity. The document also discusses differences in queries, scaling, and consistency between the two database types.
One Database Countless Possibilities for Mission-critical ApplicationsFairCom
This presentation was given during FairCom's 2016 Data Strategies Roadshow to Austin, New York City, and Salt Lake City by Evaldo Horn De Oliveira.
Database technology is difficult to predict, yet in 2016 the crossroads of SQL or NoSQL becomes more evident in many cases. This deck talks about not making a choice between one method or another, but finding a way to blend relational and non relational data within the same database.
c-treeACE V11 was announced in November 2015, and gives software developers a strong ability to build applications to use the speed of non-relational data, but have access to analyze data through SQL.
You can learn more about c-treeACE V11 at http://www.faircom.com/v11-is-here
The presentation provides an overview of NoSQL databases, including a brief history of databases, the characteristics of NoSQL databases, different data models like key-value, document, column family and graph databases. It discusses why NoSQL databases were developed as relational databases do not scale well for distributed applications. The CAP theorem is also explained, which states that only two out of consistency, availability and partition tolerance can be achieved in a distributed system.
This document provides an introduction to NoSQL databases. It begins by explaining what a database management system (DBMS) and relational database management system (RDBMS) are. It then discusses some limitations of relational databases and how NoSQL databases address those limitations by being non-relational, schema-free, and offering simple APIs. The document provides a brief history of NoSQL databases and defines what NoSQL is and why it was developed to handle large, growing amounts of unstructured data from sources like social networks. It outlines some key features of NoSQL databases.
Similar to Teoria unidad 2 Base de Datos No Relacionales (20)
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...Alex Pruden
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
"What does it really mean for your system to be available, or how to define w...Fwdays
We will talk about system monitoring from a few different angles. We will start by covering the basics, then discuss SLOs, how to define them, and why understanding the business well is crucial for success in this exercise.
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
From Natural Language to Structured Solr Queries using LLMsSease
This talk draws on experimentation to enable AI applications with Solr. One important use case is to use AI for better accessibility and discoverability of the data: while User eXperience techniques, lexical search improvements, and data harmonization can take organizations to a good level of accessibility, a structural (or “cognitive” gap) remains between the data user needs and the data producer constraints.
That is where AI – and most importantly, Natural Language Processing and Large Language Model techniques – could make a difference. This natural language, conversational engine could facilitate access and usage of the data leveraging the semantics of any data source.
The objective of the presentation is to propose a technical approach and a way forward to achieve this goal.
The key concept is to enable users to express their search queries in natural language, which the LLM then enriches, interprets, and translates into structured queries based on the Solr index’s metadata.
This approach leverages the LLM’s ability to understand the nuances of natural language and the structure of documents within Apache Solr.
The LLM acts as an intermediary agent, offering a transparent experience to users automatically and potentially uncovering relevant documents that conventional search methods might overlook. The presentation will include the results of this experimental work, lessons learned, best practices, and the scope of future work that should improve the approach and make it production-ready.
Session 1 - Intro to Robotic Process Automation.pdfUiPathCommunity
👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
📕 Detailed agenda:
What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
High performance Serverless Java on AWS- GoTo Amsterdam 2024Vadym Kazulkin
Java is for many years one of the most popular programming languages, but it used to have hard times in the Serverless community. Java is known for its high cold start times and high memory footprint, comparing to other programming languages like Node.js and Python. In this talk I'll look at the general best practices and techniques we can use to decrease memory consumption, cold start times for Java Serverless development on AWS including GraalVM (Native Image) and AWS own offering SnapStart based on Firecracker microVM snapshot and restore and CRaC (Coordinated Restore at Checkpoint) runtime hooks. I'll also provide a lot of benchmarking on Lambda functions trying out various deployment package sizes, Lambda memory settings, Java compilation options and HTTP (a)synchronous clients and measure their impact on cold and warm start times.
The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
Must Know Postgres Extension for DBA and Developer during MigrationMydbops
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/
This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...Jason Yip
The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...DanBrown980551
This LF Energy webinar took place June 20, 2024. It featured:
-Alex Thornton, LF Energy
-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
-Discovery and client registration, emphasizing transparent processes and secure and private access
-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
-Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data
2. Criterios de Evaluación
Asistencia - 10% - (lista)
Mapa Conceptual Ilustrativo
“Base de Datos No Relacionales & Base de Datos
Referenciales”
35% (lista de cotejo)
Tabla Comparativa
“Base de Datos No Relacionales Orientadas a
Documentos, Clave-Valor, Grafos, Columnas”
35% (lista de cotejo)
✓ Evaluación – 20% (Cuestionario Automatizado
5. Introducción.
De las mas importantes.
Han marcado la pauta dentro
de la era digital.
Presentes en aplicaciones
móviles.
Presentes en software de los
ordenadores.
5
6. Introducción.
En los tiempos del Big Data, es decir, nuestro día
común y corriente, el volumen de datos que
generamos no deja de crecer. Esto significa que
los datos que debemos gestionar y considerar
también es cada vez mayor.
Nuestros sistemas demandan grandes
capacidades de almacenamiento y análisis a alta
velocidad.
6
7. Base de Datos No SQL - Documentos
¿Qué son las bases de
datos NoSQL
documentales?
7
8. Base de Datos No SQL - Documentos
Una base de datos documental, también
denominada base de datos orientada a
documentos, es un subconjunto de un tipo de base
de datos construida bajo NoSQL. Las BBDD
documentales son aliados fundamentales en los
que podemos confiar para el manejo de
voluminosas cantidades de información.
8
9. Base de Datos No SQL - Documentos
Conjunto de información
estructurada en registros.
Almacenadas en un soporte
electrónico.
Registros = unidad autónoma.
9
Utilización de documentos.
Documentos = registros y datos
asociados.
Documentos de texto, archivos
XML o JSON.
Datos semiestructurados
10. Base de Datos No SQL - Documentos
¿Qué beneficios nos
brindas estas base de
datos NoSQL
documentales?
10
11. Base de Datos No SQL - Documentos
Versatilidad: La dinámica que ofrecen estos modelos de bases de
datos permite que su modificación sea más sencilla que la de los
modelos relacionales.
Flexibilidad: Estas nos abren las posibilidades de incorporar de manera
flexible y dinámica modelos nuevos de análisis de datos para lo que
necesitemos en nuestro día a día.
Escritura rápida: Esto permite asegurar que las escrituras de datos
siempre serán rápidas sin importar la existencia de una falla de
hardware o de la red.
Rendimiento: Necesitamos consultas de alta velocidad con potentes
motores de búsqueda con propiedades de indexación.
11
12. Base de Datos No SQL - Documentos
¿Cuáles son las Base
de Datos No SQL mas
populares?
12
21. Introducción.
NoSQL.
Simple almacenamiento.
Gran funcionalidad.
Aprecio de los
desarrolladores.
Alta eficacia en lectura y
escritura de datos.
21
22. Base de Datos No SQL – clave-valor
¿Qué son las bases de
datos NoSQL Clave-
Valor?
22
23. Base de Datos No SQL – clave-valor
Una base de datos clave valor (Key-Value) es un tipo de base
de datos NoSQL que funciona con un modelo simple de claves
y valores. Esto se refiere al hecho de que la base de datos
almacena en pares clave/valor.
23
24. 24
• Clave sintética
• Clave autogenerada
• Clave de diversos
formatos
• Clave única
• Valores con estructura
simple
• Valores con diferentes
formatos
• Diccionarios
Base de Datos No SQL – clave-valor
25. 25
Aplicaciones de una Base de
Datos No SQL – clave-valor
• Get – Put – Delete.
• Vincularla con diversos proyectos.
• Independencia de elementos
• E-shopping.
• Facilidad de escalada.
• Redundancia incorporada.
26. Base de Datos No SQL – clave valor
¿Cuáles son las
ventajas y desventajas
de las Base de Datos
No SQL clave-valor?
26
27. Base de Datos No SQL – clave-valor
Ventajas
› Almacenan los datos en diccionarios.
› Velocidad y escalabilidad.
Desventajas
› Consultas básicas.
› Configuración personalizada.
› Parte de la clave primaria
27
28. Base de Datos No SQL – clave valor
¿Cuáles son las Base
de Datos No SQL
clave-valor mas
populares?
28
36. Introducción.
NoSQL.
Ganando público.
Modelado de datos.
Potentes.
Representación del mundo real.
Flexibilidad.
Representación del consumo de
datos.
Compresión óptima.
Aprovechamiento máximo.
36
37. Base de Datos No SQL – Grafos
¿Qué son las bases de
datos NoSQL gráfos?
37
38. Base de Datos No SQL - Grafos
Un grafo es una
composición de un
conjunto de objetos
llamados nodos conectados
a través de una serie de
aristas. En los nodos están
conformados por
información y las aristas
que conectan los nodos nos
permiten entender las
relaciones que existen entre
los nodos.
38
39. Base de Datos No SQL - Grafos
Diferentes tipos de grafos:
Relaciones dirigidas o no.
Multiplicidad de relaciones entre nodos.
Distinta aridad de relaciones.
Representación complejas entre datos.
Carecen de esquemas.
Gran flexibilidad.
Grandes volúmenes de datos.
Diversidad de métodos analíticos y consulta
Web Blogs
Twitter
39
41. Base de Datos No SQL – grafos
¿Cuáles son las
ventajas y desventajas
de las Base de Datos
No SQL - grafos?
41
42. Base de Datos No SQL – grafos
Ventajas
› Rendimiento.
› Flexibilidad.
› Rapidez.
Desventajas
› Dificultades con respecto a la atomicidad y sus
patrones de estandarización.
› Cuando se realizan particiones en función de
propiedades locales pueden presentarse
dificultades similares a las de una base de datos
relacional. 42
43. Base de Datos No SQL – grafos
¿Cuáles son los
usos de la Base de
Datos No SQL
de grafos?
43
44. Base de Datos No SQL – grafos
Detección de
fraude
44
Big Data
Rendimiento en
Redes Sociales
45. Base de Datos No SQL – grafos
¿Cuáles son las Base
de Datos No SQL
de grafos mas
populares?
45
52. Base de Datos No SQL – Columnas
¿Qué son las bases de
datos NoSQL -
Columnas?
52
53. Distribución común en filas
SGBD crea una línea para cada entrada.
Los datos de cada entrada están
dispuestos uno al lado del otro 53
Base de Datos No SQL – Columnas
Distribución en columnas
Por cada entrada, hay una columna.
Los datos de cada entrada están
dispuestos uno debajo del otro.
FILA
COLUMNA
54. 54
Base de Datos No SQL – Columnas
Sistema orientado en filas
Sistema orientado en columnas
Número Apellido Nombre Clave
0010 Nolasco Obed 3FN-Z768
0011 Lavalle Beti 7TR-K345
0012 Larios Citlali 8NN-R266
Número 0010 0011 0012
Apellido Nolasco Lavalle Larios
Nombre Obed Beti Citlali
Clave 3FN-Z768 7TR-K345 8NN-R266
55. 55
Base de Datos No SQL – Columnas
En el disco duro, sin embargo, los datos se muestran unidimensionales, es
decir, se representan de forma sucesiva.
Sistema orientado en filas
La base de datos columnar también almacena la información de forma
sucesiva, pero al organizar los datos de otra forma también resulta una
secuencia de datos distinta.
Sistema orientado en columnas
0010, Nolasco, Oded, 3FN-Z768; 0011, Lavalle, Beti, 7TR-K345; 0012, Larios, Citlali, 8NN-R266
0010, 0011, 0012; Nolasco, Lavalle, Larios; Obed, Beti, Citlali; 3FN-Z768, 7TR-K345, 8NN-R266
56. Base de Datos No SQL – Columnas
¿Cuáles son los
usos de la Base de
Datos No SQL
de Columnas?
56
57. 57
Base de Datos No SQL – Columnas
En la investigación.
Pasan por evaluaciones continuas.
Rapidez con sistemas basados en columnas.
Acceder menos al disco duro
Almacenan muy próximos
entre sí.
Se carga por bloques.
No es necesario leer la BD
completa
58. Base de Datos No SQL – Columnas
¿Cuáles son las
ventajas y desventajas
de las Base de Datos
No SQL - Columnas?
58
59. Base de Datos No SQL – Columnas
Ventajas
› Evaluación de grandes volúmenes de datos.
› La compresión: Los datos de una columna son
siempre del mismo tipo, por ejemplo, una cadena
o un entero.
Desventajas
› En las aplicaciones transaccionales los accesos son
diferentes en la mayoría de los casos: aquí, los
datos nuevos se deben distribuir a través de toda
la base de dato.
59
60. Base de Datos No SQL – Columnas
¿Cuáles son las Base
de Datos No SQL
de Columnas mas
populares?
60
68. This is a slide title
› Here you have a list of items
› And some text
› But remember not to overload your
slides with content
Your audience will listen to you or read the
content, but won’t do both.
68
70. White
Is the color of milk and fresh
snow, the color produced
by the combination of all
the colors of the visible
spectrum.
You can also split your content
Black
Is the color of ebony and of
outer space. It has been the
symbolic color of elegance,
solemnity and authority.
70
71. In two or three columns
Yellow
Is the color of gold,
butter and ripe
lemons. In the
spectrum of visible
light, yellow is found
between green and
orange.
Blue
Is the colour of the
clear sky and the
deep sea. It is
located between
violet and green on
the optical spectrum.
Red
Is the color of blood,
and because of this
it has historically
been associated
with sacrifice,
danger and courage.
71
72. A picture is
worth a
thousand
words
A complex idea can be conveyed
with just a single still image,
namely making it possible to
absorb large amounts of data
quickly.
72
80. Let’s review some concepts
Yellow
Is the color of gold, butter
and ripe lemons. In the
spectrum of visible light,
yellow is found between
green and orange.
Blue
Is the colour of the clear
sky and the deep sea. It is
located between violet
and green on the optical
spectrum.
Red
Is the color of blood, and
because of this it has
historically been
associated with sacrifice,
danger and courage.
Yellow
Is the color of gold, butter
and ripe lemons. In the
spectrum of visible light,
yellow is found between
green and orange.
Blue
Is the colour of the clear
sky and the deep sea. It is
located between violet
and green on the optical
spectrum.
Red
Is the color of blood, and
because of this it has
historically been
associated with sacrifice,
danger and courage.
80
81. You can insert graphs from Excel or Google Sheets
81
4000
3000
2000
1000
0
82. MOBILE PROJECT
Show and explain your web,
app or software projects using
these gadget templates.
82
83. TABLET PROJECT
Show and explain your web,
app or software projects using
these gadget templates.
83
84. DESKTOP PROJECT
Show and explain your
web, app or software
projects using these
gadget templates.
84
86. Credits
Special thanks to all the people who made
and released these awesome resources for
free:
› Presentation template by SlidesCarnival
› Photographs by Startupstockphotos
86
87. Presentation design
This presentation uses the following typographies:
› Titles: Hind
› Body copy: Hind
You can download the fonts on this page:
https://www.fontsquirrel.com/fonts/hind
You don’t need to keep this slide in your presentation. It’s only here to serve you as a design guide
if you need to create new slides or download the fonts to edit the presentation in PowerPoint®
87
89. Timeline
89
DEC
NOV
OCT
SEP
AUG
JUL
JUN
MAY
APR
MAR
FEB
JAN
Blue is the colour of the
clear sky and the deep
sea
Red is the colour of
danger and courage
Black is the color of
ebony and of outer
space
Yellow is the color of
gold, butter and ripe
lemons
White is the color of milk
and fresh snow
Blue is the colour of the
clear sky and the deep
sea
Yellow is the color of
gold, butter and ripe
lemons
White is the color of milk
and fresh snow
Blue is the colour of the
clear sky and the deep
sea
Red is the colour of
danger and courage
Black is the color of
ebony and of outer
space
Yellow is the color
of gold, butter and
ripe lemons
90. Roadmap
90
1 3 5
6
4
2
Blue is the colour of the
clear sky and the deep
sea
Red is the colour of
danger and courage
Black is the color of
ebony and of outer space
Yellow is the color of
gold, butter and ripe
lemons
White is the color of milk
and fresh snow
Blue is the colour of the
clear sky and the deep
sea
92. SWOT Analysis
92
STRENGTHS
Blue is the colour of
the clear sky and the
deep sea
WEAKNESSES
Yellow is the color of
gold, butter and ripe
lemons
Black is the color of
ebony and of outer
space
OPPORTUNITIES
White is the color of
milk and fresh snow
THREATS
93. Business Model Canvas
93
Key Activities
Insert your content
Key Resources
Insert your content
Value Propositions
Insert your content
Customer Relationships
Insert your content
Channels
Insert your content
Customer Segments
Insert your content
Key Partners
Insert your content
Cost Structure
Insert your content
Revenue Streams
Insert your content
95. Team Presentation
95
Imani Jackson
JOB TITLE
Blue is the colour of the
clear sky and the deep sea
Marcos Galán
JOB TITLE
Blue is the colour of the
clear sky and the deep sea
Ixchel Valdía
JOB TITLE
Blue is the colour of the
clear sky and the deep sea
Nils Årud
JOB TITLE
Blue is the colour of the
clear sky and the deep sea
98. SlidesCarnival icons are editable
shapes.
This means that you can:
● Resize them without
losing quality.
● Change fill color and
opacity.
● Change line color, width
and style.
Isn’t that nice? :)
Examples:
98
100. Now you can use any emoji as an icon!
And of course it resizes without losing quality and you can change the color.
How? Follow Google instructions
https://twitter.com/googledocs/status/730087240156643328
✋👆👉👍👤👦👧👨👩👪💃🏃💑❤
😂😉😋😒😭👶😸🐟🍒🍔💣📌📖🔨
🎃🎈🎨🏈🏰🌏🔌🔑 and many more...
100
101. Free templates for all your presentation needs
Ready to use,
professional and
customizable
100% free for personal
or commercial use
Blow your audience
away with attractive
visuals
For PowerPoint and
Google Slides