Slides from my talk at ACCU2011 in Oxford on 16th April 2011. A whirlwind tour of the non-relational database families, with a little more detail on Redis, MongoDB, Neo4j and HBase.
Infinispan, Data Grids, NoSQL, Cloud Storage and JSR 347Manik Surtani
Manik Surtani is the founder and project lead of Infinispan, an open source data grid platform. He discussed data grids, NoSQL, and their role in cloud storage. Data grids evolved from distributed caches to provide features like querying, task execution, and co-location control. NoSQL systems are alternative data storage that is scalable and distributed but lacks relational structure. JSR 347 aims to standardize data grid APIs for the Java platform. Infinispan implements JSR 107 and will support JSR 347, acting as the reference backend for Hibernate OGM.
The document provides an introduction to Hadoop. It discusses how Google developed its own infrastructure using Google File System (GFS) and MapReduce to power Google Search due to limitations with databases. Hadoop was later developed based on these Google papers to provide an open-source implementation of GFS and MapReduce. The document also provides overviews of the HDFS file system and MapReduce programming model in Hadoop.
Big Data and NoSQL for Database and BI ProsAndrew Brust
This document provides an agenda and overview for a conference session on Big Data and NoSQL for database and BI professionals held from April 10-12 in Chicago, IL. The session will include an overview of big data and NoSQL technologies, then deeper dives into Hadoop, NoSQL databases like HBase, and tools like Hive, Pig, and Sqoop. There will also be demos of technologies like HDInsight, Elastic MapReduce, Impala, and running MapReduce jobs.
Infinispan, transactional key value data grid and nosql databaseAlexander Petrov
The document discusses key topics related to distributed caching including cache technologies, consistency models, performance considerations, and challenges in introducing distributed caching to existing systems. It provides examples of how reference data and transactional data differ in maximum reads and writes per second. The document also covers cache eviction policies, transactions, and mixing technology stacks.
NoSQL databases such as Redis, MongoDB and Cassandra are emerging as a compelling choice for many applications. They can simplify the persistence of complex data models and offer significantly better scalability and performance. However, using a NoSQL database means giving up the benefits of the relational model such as SQL, constraints and ACID transactions. For some applications, the solution is polyglot persistence: using SQL and NoSQL databases together.
In this talk, you will learn about the benefits and drawbacks of polyglot persistence and how to design applications that use this approach. We will explore the architecture and implementation of an example application that uses MySQL as the system of record and Redis as a very high-performance database that handles queries from the front-end. You will learn about mechanisms for maintaining consistency across the various databases.
Polyglot Persistence - Two Great Tastes That Taste Great TogetherJohn Wood
The days of the relational database being a one-stop-shop for all of your persistence needs are over. Although NoSQL databases address some issues that can’t be addressed by relational databases, the opposite is true as well. The relational database offers an unparalleled feature set and rock solid stability. One cannot underestimate the importance of using the right tool for the job, and for some jobs, one tool is not enough. This talk focuses on the strength and weaknesses of both relational and NoSQL databases, the benefits and challenges of polyglot persistence, and examples of polyglot persistence in the wild.
These slides were presented at WindyCityDB 2010.
Big Data and Hadoop - History, Technical Deep Dive, and Industry TrendsEsther Kundin
An overview of the history of Big Data, followed by a deep dive into the Hadoop ecosystem. Detailed explanation of how HDFS, MapReduce, and HBase work, followed by a discussion of how to tune HBase performance. Finally, a look at industry trends, including challenges faced and being solved by Bloomberg for using Hadoop for financial data.
Developing polyglot persistence applications (SpringOne China 2012)Chris Richardson
The document discusses using Redis to optimize queries in polyglot persistence applications by creating materialized views that denormalize and index data from a relational database into Redis for faster access. It provides an example of using Redis sorted sets to index available restaurant data from a MySQL database in a way that allows fast retrieval of open restaurants for a given zip code and time. The approach simplifies queries by eliminating joins and reducing data returned through concatenation and indexing techniques.
Solr cloud the 'search first' nosql database extended deep divelucenerevolution
Presented by Mark Miller, Software Engineer, Cloudera
As the NoSQL ecosystem looks to integrate great search, great search is naturally beginning to expose many NoSQL features. Will these Goliath's collide? Or will they remain specialized while intermingling – two sides of the same coin.
Come learn about where SolrCloud fits into the NoSQL landscape. What can it do? What will it do? And how will the big data, NoSQL, Search ecosystem evolve. If you are interested in Big Data, NoSQL, distributed systems, CAP theorem and other hype filled terms, than this talk may be for you.
In DiDi Chuxing Company, which is China’s most popular ride-sharing company. we use HBase to serve when we have a bigdata problem.
We run three clusters which serve different business needs. We backported the Region Grouping feature back to our internal HBase version so we could isolate the different use cases.
We built the Didi HBase Service platform which is popular amongst engineers at our company. It includes a workflow and project management function as well as a user monitoring view.
Internally we recommend users use Phoenix to simplify access.even more,we used row timestamp;multidimensional table schema to slove muti dimension query problems
C++, Go, Python, and PHP clients get to HBase via thrift2 proxies and QueryServer.
We run many important buisness applications out of our HBase cluster such as ETA/GPS/History Order/API metrics monitoring/ and Traffic in the Cloud. If you are interested in any aspects listed above, please come to our talk. We would like to share our experiences with you.
HBaseCon 2012 | You’ve got HBase! How AOL Mail Handles Big DataCloudera, Inc.
The AOL Mail Team will discuss our implementation of HBase for two large scale applications: an anti-abuse mechanism and a user-visible API. We will provide an overview of how and why HBase and Hadoop were incorporated into the massive and diverse technology stack that is the nearly 20-year-old AOL Mail system and the history of how we took our HBase/Hadoop apps through our traditional process of design, to development, through QA, and into production. We will explain how our practical approach to HBase has evolved over time, and we will discuss our lessons learned and some of our techniques and tools developed via our iterative dev/qa and operational processes. We will explain the pain-points we have experienced with erratic usage and edge-cases, and how we address problems when we run across them.
The Evolution of Open Source DatabasesIvan Zoratti
The document provides an overview of the evolution of open source databases from the past to present and future. It discusses the early days of navigational and hierarchical databases. It then covers the development of relational databases and SQL. It outlines the rise of open source databases like MySQL, PostgreSQL, and SQLite. It also summarizes the emergence of NoSQL databases and NewSQL systems to handle big data and cloud computing. The document predicts continued development and blending of features between SQL, NoSQL, and NewSQL databases.
HBaseCon 2015 General Session: Zen - A Graph Data Model on HBaseHBaseCon
Zen is a storage service built at Pinterest that offers a graph data model of top of HBase and potentially other storage backends. In this talk, Zen's architects go over the design motivation for Zen and describe its internals including the API, type system, and HBase backend.
Building Google-in-a-box: using Apache SolrCloud and Bigtop to index your big...rhatr
You’ve got your Hadoop cluster, you’ve got your petabytes of unstructured data, you run mapreduce jobs and SQL-on-Hadoop queries. Something is still missing though. After all, we are not expected to enter SQL queries while looking for information on the web. Altavista and Google solved it for us ages ago. Why are we still requiring SQL or Java certification from our enterprise bigdata users? In this talk, we will look into how integration of SolrCloud into Apache Bigtop is now enabling building bigdata indexing solutions and ingest pipelines. We will dive into the details of integrating full-text search into the lifecycle of your bigdata management applications and exposing the power of Google-in-a-box to all enterprise users, not just a chosen few data scientists.
This document provides an introduction to relational databases, NoSQL databases, and data in general. It includes the following:
- An overview of relational databases and their ACID properties. Relational databases are best for structured, centralized data and scale vertically.
- A survey of several popular NoSQL databases like MongoDB, Cassandra, Redis, and HBase. NoSQL databases are best for unstructured, large quantities of data and scale horizontally.
- General advice that the data and query models, durability needs, scalability needs, and consistency requirements should determine the best database choice. Trying different options is recommended.
This is the presentation at Percona Live 2015 on MySQL, MariaDB and Percona Orchestration on bare metal, virtualised environments and clouds (AWS and OpenStack).
Cloud Computing and the Microsoft Developer - A Down-to-Earth AnalysisAndrew Brust
Slides from my Keynote at Visual Studio Live Las Vegas 2011 (Day 2).
Closely compares Azure to AWS, and discusses Force.com, Google, Rackspace, VMWare and Red Hat.
Discussion includes capabilities, pricing, strategy.
This is an introduction to relational and non-relational databases and how their performance affects scaling a web application.
This is a recording of a guest Lecture I gave at the University of Texas school of Information.
In this talk I address the technologies and tools Gowalla (gowalla.com) uses including memcache, redis and cassandra.
Find more on my blog:
http://schneems.com
NBITS is a best hadoop training institute providing customer project-based Training and Placements in Big Data Hadoop. NBITS provides Hadoop Training in Hyderabad by Real time experts faculty with 10+ yrs Experience.
A brief overview of currently popular & available key/value, column oriented & document oriented databases, along with implementation suggestions for the CakePHP web application framework.
Relational Model and Relational Algebra - Lecture 3 - Introduction to Databas...Beat Signer
The document discusses Edgar Codd's relational model for data management. It describes how Codd developed the relational model while working at IBM and published a seminal paper on it in 1970. It also discusses how IBM initially did not implement the model, but later developed prototypes like System R that helped drive commercial relational database management systems. The document provides an introduction to key concepts of the relational model like relational algebra operations, relations, attributes, keys and database schemas.
The document discusses relational database design and normalization. It covers first normal form, functional dependencies, and decomposition. The goal of normalization is to avoid data redundancy and anomalies. First normal form requires attributes to be atomic. Functional dependencies specify relationships between attributes that must be preserved. Decomposition breaks relations into smaller relations while maintaining lossless join properties. Higher normal forms like Boyce-Codd normal form and third normal form further reduce redundancy.
Relational databases vs Non-relational databasesJames Serra
There is a lot of confusion about the place and purpose of the many recent non-relational database solutions ("NoSQL databases") compared to the relational database solutions that have been around for so many years. In this presentation I will first clarify what exactly these database solutions are, compare them, and discuss the best use cases for each. I'll discuss topics involving OLTP, scaling, data warehousing, polyglot persistence, and the CAP theorem. We will even touch on a new type of database solution called NewSQL. If you are building a new solution it is important to understand all your options so you take the right path to success.
The document discusses the representation of social groups in the film "The Catch". It portrays school children, with the protagonist Gemma being a student, and caretakers, with the loner caretaker character seeking comfort in young girls. It represents typical thriller social groups - the male pedophile caretaker and the helpless school girl victim. It also discusses how the film uses themes of paranoia by contradicting the assumption that schools are safe, and moral panics by locating the pedophile character in a school to effectively evoke outrage.
This document discusses raising godly children and serving God as families. It provides examples of family ministries like caring for orphans and participating in mission trips. It emphasizes that families that serve God together stay together. It encourages parenting through love instead of expectations and avoiding outsourcing the spiritual formation of children. Parents are advised to create happy homes, teach children from a young age, and be role models by living according to their values.
This document outlines the historic campus master plans of the University of California, Berkeley from 1865 to 1962. It describes three eras led by Frederick Law Olmsted during the Picturesque Era from 1865-1914, John Galen Howard during the Beaux-Arts Era from 1914-1962, and Thomas Church during the Modern Era from 1962 onward. It also highlights some of the campus's defining open spaces and landmarks that were planned during these eras, such as Sproul Plaza, the Campanile, and Strawberry Creek.
This document discusses Docker, a tool for deploying applications as portable, self-sufficient containers. It provides an overview of Docker components like the Engine, Hub, Compose and Swarm. Key aspects of Docker like namespaces, control groups and union file systems that enable isolation and resource management are explained. The document also covers building Docker images using Dockerfiles, running containers, linking containers, managing storage and deploying applications on Docker.
The document discusses the representation of social groups in the film "The Catch". It portrays school children, with the protagonist Gemma being a student, and caretakers, with the loner caretaker character seeking comfort in young girls. It represents typical thriller social groups - the male pedophile caretaker and the helpless school girl victim. Paranoia is a theme, with Gemma sensing someone watching her to create tension. Media typically portrays pedophiles negatively as the most hated people to elicit empathy, and moral panics can be inspired by violating standards, like the Ian Huntley case of school girls, similar to the caretaker's sexually motivated killings in a school setting.
Maximize How You Individualize: because the Journey and Outcome Matter Nicholas Kontopoulos
According to research from the Corporate Executive Board, 57% of the buying process is being completed before the first interaction with a sales person.
In recent years, a fundamental sea change has been occurring between buyers and sellers, with the former now ceasing control of the buying process. This paradigm shift has been digitally powered with todays buyers only one touch away from connecting with content or peers that can help guide them on their purchasing journey.
This presentation will explore the challenges that not only lay ahead for todays marketers, but also explore some of the ways in which innovative brands are adapting to this 'New Reality’.
Este documento explica cómo calcular la altura, los lados, el área y el perímetro de un triángulo rectángulo dado. Proporciona las fórmulas del teorema de la altura, teorema de Pitágoras, área y perímetro de un triángulo rectángulo. Luego aplica estas fórmulas a un triángulo específico para calcular su perímetro.
The sermon discusses the presentation of Jesus in the temple as described in Luke 2:22-38. It notes that Mary and Joseph marveled at the good news they received about Jesus. However, Simeon then revealed that the good news would also be bad news for some, as Jesus' coming would cause division. Anna later confirmed that the bad news was ultimately good news, promising redemption. The sermon emphasizes that while the good news of Christmas was joyous, it was also costly, bringing hope, joy and peace through God coming near as Immanuel.
The document provides an overview of SQL vs NoSQL databases. It discusses how RDBMS systems focus on ACID properties to ensure consistency but sacrifice availability and scalability. NoSQL systems embrace the CAP theorem, prioritizing availability and partition tolerance over consistency to better support distributed and cloud-scale architectures. The document outlines different NoSQL database models and how they are suited for high volume operations through an asynchronous and eventually consistent approach.
This document provides an overview and summary of key concepts related to advanced databases. It discusses relational databases including MySQL, SQL, transactions, and ODBC. It also covers database topics like triggers, indexes, and NoSQL databases. Alternative database systems like graph databases, triplestores, and linked data are introduced. Web services, XML, and data journalism are also briefly summarized. The document provides definitions and examples of these technical database terms and concepts.
This document provides a summary of a presentation on Big Data and NoSQL databases. It introduces the presenters, Melissa Demsak and Don Demsak, and their backgrounds. It then discusses how data storage needs have changed with the rise of Big Data, including the problems created by large volumes of data. The presentation contrasts traditional relational database implementations with NoSQL data stores, identifying five categories of NoSQL data models: document, key-value, graph, and column family. It provides examples of databases that fall under each category. The presentation concludes with a comparison of real-world scenarios and which data storage solutions might be best suited to each scenario.
Oracle Week 2016 - Modern Data ArchitectureArthur Gimpel
This document discusses modern operational data architectures and the use of both relational and NoSQL databases. It provides an overview of relational databases and their ACID properties. While relational databases dominate the market, they have limitations around scalability, flexibility, and performance. NoSQL databases offer alternatives like horizontal scaling and flexible schemas. Key-value stores are best for caching, sessions, and serving data, while document stores are popular for hierarchical and search use cases. Graph databases excel at link analysis. The document advocates a polyglot persistence approach using multiple database types according to their strengths. It provides examples of search architectures using both database-centric and application-centric distribution approaches.
The document discusses the rapid growth of data on the web and how NoSQL databases provide an alternative to traditional relational databases by being able to handle massive amounts of unstructured and semi-structured data across a large number of servers in a simple and scalable way. It reviews different types of NoSQL databases like key-value stores, document databases, and graph databases and provides examples of popular NoSQL databases like MongoDB, CouchDB, HBase, and Neo4j that are being used by large companies to store and query large datasets.
Dropping ACID: Wrapping Your Mind Around NoSQL DatabasesKyle Banerjee
This document discusses NoSQL databases as an alternative to traditional relational databases. It provides an overview of different types of NoSQL databases like document stores, wide column stores, key-value stores and graph databases. It also discusses advantages of NoSQL databases like horizontal scalability and ease of use with large amounts of unstructured data, as well as disadvantages like lack of transactions and joins. The document recommends choosing a database based on the type of queries, data size, read/write needs, and whether the data needs to be accessed by other applications.
The document introduces Datomic, an immutable database with an architecture that separates reads, writes, and storage. It has several key benefits, including built-in data distribution and caching, elastic scaling, and a data model based on immutable facts rather than embedded structures. The programming model uses a peer embedded in applications to pull indexed data as needed, and supports transactional updates and time-based queries using a declarative Datalog language.
The document discusses NoSQL databases, describing their characteristics like being non-relational, scalable, and schema-free. It covers different types of NoSQL databases like key-value stores, wide column stores, document stores, and graph databases. The document also discusses where NoSQL databases are particularly useful compared to relational databases and gives examples of companies using NoSQL.
An overview of various database technologies and their underlying mechanisms over time.
Presentation delivered at Alliander internally to inspire the use of and forster the interest in new (NOSQL) technologies. 18 September 2012
This document provides an overview of NoSQL databases. It discusses that NoSQL databases are non-relational and do not follow the RDBMS principles. It describes some of the main types of NoSQL databases including document stores, key-value stores, column-oriented stores, and graph databases. It also discusses how NoSQL databases are designed for massive scalability and do not guarantee ACID properties, instead following a BASE model ofBasically Available, Soft state, and Eventually Consistent.
The document discusses NoSQL databases and their advantages compared to SQL databases. It defines NoSQL as any database that is not relational and describes the main categories of NoSQL databases - key-value stores, document databases, wide column stores like BigTable, and graph databases. It also covers common use cases for different NoSQL databases and examples of companies using NoSQL technologies like MongoDB, Cassandra, and HBase.
This document provides an introduction to Microsoft Azure DocumentDB. It discusses how DocumentDB is a non-relational or NoSQL database that stores data in JSON documents. It also overview how DocumentDB provides scalability, high availability, and fast performance for large document workloads. Key features of DocumentDB discussed include its resource and interaction models, indexing, consistency options, querying capabilities, and support for JavaScript transactions.
Cassandra consistently outperforms other NoSQL databases in throughput and scalability according to various benchmark tests, but has higher read latencies. MongoDB typically has the worst performance in terms of latency. The best database depends on application requirements - no single NoSQL database is best for all use cases. Combining database types, such as using Cassandra for analytics and an RDBMS for transactions, can leverage each database's strengths.
Colorado Springs Open Source Hadoop/MySQL David Smelker
This document discusses MySQL and Hadoop integration. It covers structured versus unstructured data and the capabilities and limitations of relational databases, NoSQL, and Hadoop. It also describes several tools for integrating MySQL and Hadoop, including Sqoop for data transfers, MySQL Applier for streaming changes to Hadoop, and MySQL NoSQL interfaces. The document outlines the typical life cycle of big data with MySQL playing a role in data acquisition, organization, analysis, and decisions.
Technical overview of three of the most representative KeyValue Stores: Cassandra, Redis and CouchDB. Focused on Ruby and Ruby on Rails developement, this talk shows how to solve common problems, the most popular libraries, benchmarking and the best use case for each one of them.
This talk was part of the Conferencia Rails 2009, Madrid, Spain.
http://app.conferenciarails.org/talks/43-key-value-stores-conviertete-en-un-jedi-master
Big Data Developers Moscow Meetup 1 - sql on hadoopbddmoscow
This document summarizes a meetup about Big Data and SQL on Hadoop. The meetup included discussions on what Hadoop is, why SQL on Hadoop is useful, what Hive is, and introduced IBM's BigInsights software for running SQL on Hadoop with improved performance over other solutions. Key topics included HDFS file storage, MapReduce processing, Hive tables and metadata storage, and how BigInsights provides a massively parallel SQL engine instead of relying on MapReduce.
Big Data is the reality of modern business: from big companies to small ones, everybody is trying to find their own benefit. Big Data technologies are not meant to replace traditional ones, but to be complementary to them. In this presentation you will hear what is Big Data and Data Lake and what are the most popular technologies used in Big Data world. We will also speak about Hadoop and Spark, and how they integrate with traditional systems and their benefits.
This document provides an overview and comparison of SQL and NoSQL databases. It begins by defining SQL and NoSQL databases and listing some of their key characteristics. SQL databases are relational, use structured query language (SQL), and have ACID transactions, while NoSQL databases are non-relational, use dynamic schemas, and have BASE consistency. The document then discusses some examples of SQL and NoSQL databases and different NoSQL database types like document stores, key-value stores, and column stores. It also covers MongoDB specifically, providing definitions and examples.
Similar to Non-Relational Databases at ACCU2011 (20)
Cracking AI Black Box - Strategies for Customer-centric Enterprise ExcellenceQuentin Reul
The democratization of Generative AI is ushering in a new era of innovation for enterprises. Discover how you can harness this powerful technology to deliver unparalleled customer value and securing a formidable competitive advantage in today's competitive market. In this session, you will learn how to:
- Identify high-impact customer needs with precision
- Harness the power of large language models to address specific customer needs effectively
- Implement AI responsibly to build trust and foster strong customer relationships
Whether you're at the early stages of your AI journey or looking to optimize existing initiatives, this session will provide you with actionable insights and strategies needed to leverage AI as a powerful catalyst for customer-driven enterprise success.
How UiPath Discovery Suite supports identification of Agentic Process Automat...DianaGray10
📚 Understand the basics of the newly persona-based LLM-powered Agentic Process Automation and discover how existing UiPath Discovery Suite products like Communication Mining, Process Mining, and Task Mining can be leveraged to identify APA candidates.
Topics Covered:
💡 Idea Behind APA: Explore the innovative concept of Agentic Process Automation and its significance in modern workflows.
🔄 How APA is Different from RPA: Learn the key differences between Agentic Process Automation and Robotic Process Automation.
🚀 Discover the Advantages of APA: Uncover the unique benefits of implementing APA in your organization.
🔍 Identifying APA Candidates with UiPath Discovery Products: See how UiPath's Communication Mining, Process Mining, and Task Mining tools can help pinpoint potential APA candidates.
🔮 Discussion on Expected Future Impacts: Engage in a discussion on the potential future impacts of APA on various industries and business processes.
Enhance your knowledge on the forefront of automation technology and stay ahead with Agentic Process Automation. 🧠💼✨
Speakers:
Arun Kumar Asokan, Delivery Director (US) @ qBotica and UiPath MVP
Naveen Chatlapalli, Solution Architect @ Ashling Partners and UiPath MVP
Generative AI technology is a fascinating field that focuses on creating comp...Nohoax Kanont
Generative AI technology is a fascinating field that focuses on creating computer models capable of generating new, original content. It leverages the power of large language models, neural networks, and machine learning to produce content that can mimic human creativity. This technology has seen a surge in innovation and adoption since the introduction of ChatGPT in 2022, leading to significant productivity benefits across various industries. With its ability to generate text, images, video, and audio, generative AI is transforming how we interact with technology and the types of tasks that can be automated.
Redefining Cybersecurity with AI CapabilitiesPriyanka Aash
In this comprehensive overview of Cisco's latest innovations in cybersecurity, the focus is squarely on resilience and adaptation in the face of evolving threats. The discussion covers the imperative of tackling Mal information, the increasing sophistication of insider attacks, and the expanding attack surfaces in a hybrid work environment. Emphasizing a shift towards integrated platforms over fragmented tools, Cisco introduces its Security Cloud, designed to provide end-to-end visibility and robust protection across user interactions, cloud environments, and breaches. AI emerges as a pivotal tool, from enhancing user experiences to predicting and defending against cyber threats. The blog underscores Cisco's commitment to simplifying security stacks while ensuring efficacy and economic feasibility, making a compelling case for their platform approach in safeguarding digital landscapes.
Self-Healing Test Automation Framework - HealeniumKnoldus Inc.
Revolutionize your test automation with Healenium's self-healing framework. Automate test maintenance, reduce flakes, and increase efficiency. Learn how to build a robust test automation foundation. Discover the power of self-healing tests. Transform your testing experience.
DefCamp_2016_Chemerkin_Yury-publish.pdf - Presentation by Yury Chemerkin at DefCamp 2016 discussing mobile app vulnerabilities, data protection issues, and analysis of security levels across different types of mobile applications.
TrustArc Webinar - Innovating with TRUSTe Responsible AI CertificationTrustArc
In a landmark year marked by significant AI advancements, it’s vital to prioritize transparency, accountability, and respect for privacy rights with your AI innovation.
Learn how to navigate the shifting AI landscape with our innovative solution TRUSTe Responsible AI Certification, the first AI certification designed for data protection and privacy. Crafted by a team with 10,000+ privacy certifications issued, this framework integrated industry standards and laws for responsible AI governance.
This webinar will review:
- How compliance can play a role in the development and deployment of AI systems
- How to model trust and transparency across products and services
- How to save time and work smarter in understanding regulatory obligations, including AI
- How to operationalize and deploy AI governance best practices in your organization
Keynote : AI & Future Of Offensive SecurityPriyanka Aash
In the presentation, the focus is on the transformative impact of artificial intelligence (AI) in cybersecurity, particularly in the context of malware generation and adversarial attacks. AI promises to revolutionize the field by enabling scalable solutions to historically challenging problems such as continuous threat simulation, autonomous attack path generation, and the creation of sophisticated attack payloads. The discussions underscore how AI-powered tools like AI-based penetration testing can outpace traditional methods, enhancing security posture by efficiently identifying and mitigating vulnerabilities across complex attack surfaces. The use of AI in red teaming further amplifies these capabilities, allowing organizations to validate security controls effectively against diverse adversarial scenarios. These advancements not only streamline testing processes but also bolster defense strategies, ensuring readiness against evolving cyber threats.
It's your unstructured data: How to get your GenAI app to production (and spe...Zilliz
So you've successfully built a GenAI app POC for your company -- now comes the hard part: bringing it to production. Aparavi addresses the challenges of AI projects while addressing data privacy and PII. Our Service for RAG helps AI developers and data scientists to scale their app to 1000s to millions of users using corporate unstructured data. Aparavi’s AI Data Loader cleans, prepares and then loads only the relevant unstructured data for each AI project/app, enabling you to operationalize the creation of GenAI apps easily and accurately while giving you the time to focus on what you really want to do - building a great AI application with useful and relevant context. All within your environment and never having to share private corporate data with anyone - not even Aparavi.
"Hands-on development experience using wasm Blazor", Furdak Vladyslav.pptxFwdays
I will share my personal experience of full-time development on wasm Blazor
What difficulties our team faced: life hacks with Blazor app routing, whether it is necessary to write JavaScript, which technology stack and architectural patterns we chose
What conclusions we made and what mistakes we committed
UiPath Community Day Amsterdam: Code, Collaborate, ConnectUiPathCommunity
Welcome to our third live UiPath Community Day Amsterdam! Come join us for a half-day of networking and UiPath Platform deep-dives, for devs and non-devs alike, in the middle of summer ☀.
📕 Agenda:
12:30 Welcome Coffee/Light Lunch ☕
13:00 Event opening speech
Ebert Knol, Managing Partner, Tacstone Technology
Jonathan Smith, UiPath MVP, RPA Lead, Ciphix
Cristina Vidu, Senior Marketing Manager, UiPath Community EMEA
Dion Mes, Principal Sales Engineer, UiPath
13:15 ASML: RPA as Tactical Automation
Tactical robotic process automation for solving short-term challenges, while establishing standard and re-usable interfaces that fit IT's long-term goals and objectives.
Yannic Suurmeijer, System Architect, ASML
13:30 PostNL: an insight into RPA at PostNL
Showcasing the solutions our automations have provided, the challenges we’ve faced, and the best practices we’ve developed to support our logistics operations.
Leonard Renne, RPA Developer, PostNL
13:45 Break (30')
14:15 Breakout Sessions: Round 1
Modern Document Understanding in the cloud platform: AI-driven UiPath Document Understanding
Mike Bos, Senior Automation Developer, Tacstone Technology
Process Orchestration: scale up and have your Robots work in harmony
Jon Smith, UiPath MVP, RPA Lead, Ciphix
UiPath Integration Service: connect applications, leverage prebuilt connectors, and set up customer connectors
Johans Brink, CTO, MvR digital workforce
15:00 Breakout Sessions: Round 2
Automation, and GenAI: practical use cases for value generation
Thomas Janssen, UiPath MVP, Senior Automation Developer, Automation Heroes
Human in the Loop/Action Center
Dion Mes, Principal Sales Engineer @UiPath
Improving development with coded workflows
Idris Janszen, Technical Consultant, Ilionx
15:45 End remarks
16:00 Community fun games, sharing knowledge, drinks, and bites 🍻
Keynote : Presentation on SASE TechnologyPriyanka Aash
Secure Access Service Edge (SASE) solutions are revolutionizing enterprise networks by integrating SD-WAN with comprehensive security services. Traditionally, enterprises managed multiple point solutions for network and security needs, leading to complexity and resource-intensive operations. SASE, as defined by Gartner, consolidates these functions into a unified cloud-based service, offering SD-WAN capabilities alongside advanced security features like secure web gateways, CASB, and remote browser isolation. This convergence not only simplifies management but also enhances security posture and application performance across global networks and cloud environments. Discover how adopting SASE can streamline operations and fortify your enterprise's digital transformation strategy.
The Challenge of Interpretability in Generative AI Models.pdfSara Kroft
Navigating the intricacies of generative AI models reveals a pressing challenge: interpretability. Our blog delves into the complexities of understanding how these advanced models make decisions, shedding light on the mechanisms behind their outputs. Explore the latest research, practical implications, and ethical considerations, as we unravel the opaque processes that drive generative AI. Join us in this insightful journey to demystify the black box of artificial intelligence.
Dive into the complexities of generative AI with our blog on interpretability. Find out why making AI models understandable is key to trust and ethical use and discover current efforts to tackle this big challenge.
Discovery Series - Zero to Hero - Task Mining Session 1DianaGray10
This session is focused on providing you with an introduction to task mining. We will go over different types of task mining and provide you with a real-world demo on each type of task mining in detail.
3. Me
• Director of Engineering at MyDrive
• Hands-on coding in Ruby, C++ & others
• Big data, SW architecture, robustness, tdd,
devops, data analysis
• Background of SW for telecoms, mobile,
embedded
• @gavinheavyside
4. MyDrive Solutions
• Driver behaviour analysis and scoring for
telematics-based insurance
• Large-scale geospatial processing of GPS
and map data
• Relational DBs - PostgreSQL, MySQL
• Non-relational DBs - Redis, HBase
• Big Data tools - Hadoop
• Built on Linux and open-source stack
45. redis
• By Salvatore Sanfillipo (@antirez)
• Sponsored by VMware
• data-structure server
• strings, hashes, lists
• sets, sorted sets
• All operations in memory, backed by disk
13 rules, numbered 0 to 12\nNo popular DBMS is actually ‘relational’ by 12 rules - they all break some of them\nLeading commercial - Oracle, MS, IBM (DB2)\nLeading open-source - MySQL, PostgreSQL, SQLite\n
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If one part of transaction fails, it all fails, DB left unchanged.\nFailures: HW, system, DB (disk etc), application (violate constraints on data)\n
The DB will enforce consistency and relationships/constraints that have been specified in the schema - everything else is the responsibility of the application\n
Dirty reads - allow other transactions to read, but not modify uncommitted data - improve performance\n
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DB creates new version of data for a TX\nOther TXes read the old version until TX completed.\nMVCC used by some non-relational databases\n
Usually use a transaction log that can be replayed to rebuild data in event of failure.\n
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What most of these companies have in common is scale\nHow would an RDBMS handle the size of data they deal with?\nMost of the big companies have built their own solutions.\nMost of them also use RDBMSes - Facebook is huge MySQL user.\n
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Scaling - RDBMs don’t scale linearly - big box == $$$$\ne.g. Graph relationships don’t map to tables & rows easily\nSemi/Unstructured data, lots of columns, lots of nulls\n
Caching - e.g. memcacheDB, store common queries in memory\ndenormalise - add redundant data, grouped data to reduce table joins - reduce load on physical hardware - improve locality of reference\nSo... you choose a distributed NOSQL fancy modern DB\n
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Not really...\n
C - all nodes see same data at the same time\nA - survivors continue to operate when nodes fail\nP - system continues to operate despite message loss between nodes\nMany systems relax consistency\n
Also by Eric Brewer \nBASE system relaxes the C in CAP\nBA - might lose access to some data if nodes fail\nSS - System state might change over time without input (eventual consistency, propagation)\n
Different ways to consider whether a write has succeeded, whether new value is returned.\n
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Consistent Smashing - video from Basho/Riak\n
Lots of overlap between families - esp. column & key-value/DHT\n
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Schema-less way of looking at data as documents rather than fields - all related data in document. \nMaps very well to a lot of applications\n
huMONGOus\n10gen\n
Can be ACID if using replication for durability\n
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Object mapper - not ORM\n
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FlockDB - Twitter, social graph - simpler than neo4j\nNeo4j - dual open-source/commercial license\nHama - apache project\n
Tokyo Tyrant - network access protocol for Tokyo Cabinet DB\nVoldemort - LinkedIn\n
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Can be ACID if aof fsyncs all the time\n
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replication non-blocking on master. Writes will work even if slave blocked.\nReplication for scaling (read-only slaves) or for redundancy.\nAOF log - everything that changes the dataset.\nIf server crashes redis replays the AOF\nBGREWRITEAOF to optimize AOF - minimum steps to rebuild dataset in memory\nconfigurable fsync options - every command, every second, never\n\n
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Oracle Berkeley DB, Berkeley DB Java, Berkeley DB XML\nMemcache + Berkeley DB = MemcacheDB, a bit like Redis, for KV\n\n
OSDI 2006 (MapReduce was 2004)\n
Bigtable - column families, distributed, scale\n
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Consider a whiteboard overview of Hadoop here. \nReal-time (low-latency) as opposed to Hadoop & mapreduce batch jobs. \nNot ACID - effect of distributed writes on consistency and isolation of views\nRelaxes A of cap - consistent & partition tolerant\n
partitioned on row count/size\nRegion is basic unit of availability\n\n
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Queries - no support for complex queries\nCompute query in application (mapreduce, etc)\nall necessary data is denormalised in the row - wide table with lots of columns.\n“versioned get” returns older version of row\n
Couchbase - combination of CouchDB, Membase, Memcached\nKyoto Cabinet - C++ implementation by Tokyo Cabinet author.\n