Podcasts about nosql databases

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Larry Swanson, a knowledge architect, community builder, and host of the Knowledge Graph Insights podcast. They explore the relationship between knowledge graphs and ontologies, why these technologies matter in the age of AI, and how symbolic AI complements the current wave of large language models. The conversation traces the history of neuro-symbolic AI from its origins at Dartmouth in 1956 through the semantic web vision of Tim Berners-Lee, examining why knowledge architecture remains underappreciated despite being deployed at major enterprises like Netflix, Amazon, and LinkedIn. Swanson explains how RDF (Resource Description Framework) enables both machines and humans to work with structured knowledge in ways that relational databases can't, while Alsop shares his journey from knowledge management director to understanding the practical necessity of ontologies for business operations. They discuss the philosophical roots of the field, the separation between knowledge management practitioners and knowledge engineers, and why startups often overlook these approaches until scale demands them. You can find Larry's podcast at KGI.fm or search for Knowledge Graph Insights on Spotify and YouTube.Timestamps00:00 Introduction to Knowledge Graphs and Ontologies01:09 The Importance of Ontologies in AI04:14 Philosophy's Role in Knowledge Management10:20 Debating the Relevance of RDF15:41 The Distinction Between Knowledge Management and Knowledge Engineering21:07 The Human Element in AI and Knowledge Architecture25:07 Startups vs. Enterprises: The Knowledge Gap29:57 Deterministic vs. Probabilistic AI32:18 The Marketing of AI: A Historical Perspective33:57 The Role of Knowledge Architecture in AI39:00 Understanding RDF and Its Importance44:47 The Intersection of AI and Human Intelligence50:50 Future Visions: AI, Ontologies, and Human BehaviorKey Insights1. Knowledge Graphs Combine Structure and Instances Through Ontological Design. A knowledge graph is built using an ontology that describes a specific domain you want to understand or work with. It includes both an ontological description of the terrain—defining what things exist and how they relate to one another—and instances of those things mapped to real-world data. This combination of abstract structure and concrete examples is what makes knowledge graphs powerful for discovery, question-answering, and enabling agentic AI systems. Not everyone agrees on the precise definition, but this understanding represents the practical approach most knowledge architects use when building these systems.2. Ontology Engineering Has Deep Philosophical Roots That Inform Modern Practice. The field draws heavily from classical philosophy, particularly ontology (the nature of what you know), epistemology (how you know what you know), and logic. These thousands-year-old philosophical frameworks provide the rigorous foundation for modern knowledge representation. Living in Heidelberg surrounded by philosophers, Swanson has discovered how much of knowledge graph work connects upstream to these philosophical roots. This philosophical grounding becomes especially important during times when institutional structures are collapsing, as we need to create new epistemological frameworks for civilization—knowledge management and ontology become critical tools for restructuring how we understand and organize information.3. The Semantic Web Vision Aimed to Transform the Internet Into a Distributed Database. Twenty-five years ago, Tim Berners-Lee, Jim Hendler, and Ora Lassila published a landmark article in Scientific American proposing the semantic web. While Berners-Lee had already connected documents across the web through HTML and HTTP, the semantic web aimed to connect all the data—essentially turning the internet into a giant database. This vision led to the development of RDF (Resource Description Framework), which emerged from DARPA research and provides the technical foundation for building knowledge graphs and ontologies. The origin story involved solving simple but important problems, like disambiguating whether "Cook" referred to a verb, noun, or a person's name at an academic conference.4. Symbolic AI and Neural Networks Represent Complementary Approaches Like Fast and Slow Thinking. Drawing on Kahneman's "thinking fast and slow" framework, LLMs represent the "fast brain"—learning monsters that can process enormous amounts of information and recognize patterns through natural language interfaces. Symbolic AI and knowledge graphs represent the "slow brain"—capturing actual knowledge and facts that can counter hallucinations and provide deterministic, explainable reasoning. This complementarity is driving the re-emergence of neuro-symbolic AI, which combines both approaches. The fundamental distinction is that symbolic AI systems are deterministic and can be fully explained, while LLMs are probabilistic and stochastic, making them unsuitable for applications requiring absolute reliability, such as industrial robotics or pharmaceutical research.5. Knowledge Architecture Remains Underappreciated Despite Powering Major Enterprises. While machine learning engineers currently receive most of the attention and budget, knowledge graphs actually power systems at Netflix (the economic graph), Amazon (the product graph), LinkedIn, Meta, and most major enterprises. The technology has been described as "the most astoundingly successful failure in the history of technology"—the semantic web vision seemed to fail, yet more than half of web pages now contain RDF-formatted semantic markup through schema.org, and every major enterprise uses knowledge graph technology in the background. Knowledge architects remain underappreciated partly because the work is cognitively difficult, requires talking to people (which engineers often avoid), and most advanced practitioners have PhDs in computer science, logic, or philosophy.6. RDF's Simple Subject-Predicate-Object Structure Enables Meaning and Data Linking. Unlike relational databases that store data in tables with rows and columns, RDF uses the simplest linguistic structure: subject-predicate-object (like "Larry knows Stuart"). Each element has a unique URI identifier, which permits precise meaning and enables linked data across systems. This graph structure makes it much easier to connect data after the fact compared to navigating tabular structures in relational databases. On top of RDF sits an entire stack of technologies including schema languages, query languages, ontological languages, and constraints languages—everything needed to turn data into actionable knowledge. The goal is inferring or articulating knowledge from RDF-structured data.7. The Future Requires Decoupled Modular Architectures Combining Multiple AI Approaches. The vision for the future involves separation of concerns through microservices-like architectures where different systems handle what they do best. LLMs excel at discovering possibilities and generating lists, while knowledge graphs excel at articulating human-vetted, deterministic versions of that information that systems can reliably use. Every one of Swanson's 300 podcast interviews over ten years ultimately concludes that regardless of technology, success comes down to human beings, their behavior, and the cultural changes needed to implement systems. The assumption that we can simply eliminate people from processes misses that huma...

This show has been flagged as Explicit by the host. Research Tools Harvard Referencing - https://en.wikipedia.org/wiki/Parenthetical_referencing#Author%E2%80%93date_(Harvard_referencing) Google Notebook LM - https://notebooklm.google/ Google Scholar - https://scholar.google.co.uk/ Connected Papers - https://www.connectedpapers.com/ Zotero - https://www.zotero.org/ Databases SQL Databases - https://en.wikipedia.org/wiki/Relational_database NoSQL Databases - https://en.wikipedia.org/wiki/NoSQL Graph Databases - https://en.wikipedia.org/wiki/Graph_database Misc Borland Graphics Interface - https://en.wikipedia.org/wiki/Borland_Graphics_Interface Hough Transform - https://en.wikipedia.org/wiki/Hough_transform Joplin - https://joplinapp.org/ Provide feedback on this episode.

David Neal, developer advocate and Asana content creator, discusses his talk, The Illustrated Guide to Node.js. David shares insights from his 10-year journey with Node.js, discussing its origins, use cases, and why it remains a vital tool for developers, giving insights into JavaScript's evolution and practical tips for navigating the Node.js ecosystem. Links https://reverentgeek.com https://twitter.com/reverentgeek https://techhub.social/@reverentgeek https://staging.bsky.app/profile/reverentgeek.com https://www.threads.net/@reverentgeek https://github.com/reverentgeek https://www.youtube.com/ReverentGeek https://www.linkedin.com/in/davidneal We want to hear from you! How did you find us? Did you see us on Twitter? In a newsletter? Or maybe we were recommended by a friend? Let us know by sending an email to our producer, Emily, at emily.kochanekketner@logrocket.com (mailto:emily.kochanekketner@logrocket.com), or tweet at us at PodRocketPod (https://twitter.com/PodRocketpod). Follow us. Get free stickers. Follow us on Apple Podcasts, fill out this form (https://podrocket.logrocket.com/get-podrocket-stickers), and we'll send you free PodRocket stickers! What does LogRocket do? LogRocket provides AI-first session replay and analytics that surfaces the UX and technical issues impacting user experiences. Start understand where your users are struggling by trying it for free at [LogRocket.com]. Try LogRocket for free today.(https://logrocket.com/signup/?pdr) Special Guest: David Neal.

Mark Peco, analytics consultant and educator, joins host Andrew Miller to discuss NoSQL databases - including the types of NoSQL databases and their use cases. Visit tdwi.org/events to learn more about all the events we offer.

The text of this recording (more or less) can be found here: https://community.ibm.com/community/user/wasdevops/blogs/david-follis/2021/07/22/jakarta-batch-post-147-extras-nosql-databases Song Title: Yeshttps://www.facebook.com/conorwalshmusic/https://www.youtube.com/channel/UCDmwN1630K73E-jEMOS8azA

SQL databases have constraints on data types and consistency. NoSQL does away with them for the sake of speed, flexibility, and scale --- Send in a voice message: https://anchor.fm/tonyphoang/message

Materiały dodatkowe:Neo4j.comNeo4j console, konsola online, gdzie można się pobawić przykładowym grafem bezpośrednio z przeglądarkiNeo4j GraphGists, zestaw świetnych przykładów użycia grafówGraphGist portal, jeszcze więcej przykładów użyciaNeo4j Cypher Refcard, refcard języka CypherPanama Papers, strona główna International Consortium of Investigative Journalists z artykułami odnośnie całej aferyOffshore Leaks Database, datasety ICIJ nie tylko dla Panama Papers, ale także Paradise Papers, Bahama i Offshore Leaksryguyrg/neo4j-panama-papers, przykładowy docker z importem danych Panama Papers do bazy Wpisy na blogu teamu Neo4j odnośnie afery Panama Papers:The Panama Papers Graph Database Is Now Available for DownloadHow the ICIJ Used Neo4j to Unravel the Panama PaperAnalyzing the Panama Papers with Neo4j: Data Models, Queries & MoreThe Panama Papers: Why It Couldn’t Have Happened Ten Years AgoNa koniec polecę jeszcze darmową książeczkę od O'Reilly Media, Graph Databases. Można ją pobrać ze strony https://graphdatabases.com.

Breaking away from the interview format, Wes and Kevin deep dive into SQL vs noSQL databases.Show notes:ACID compliance - https://mariadb.com/resources/blog/acid-compliance-what-it-means-and-why-you-should-careCAP theorem https://www.ibm.com/cloud/learn/cap-theoremhttps://mwhittaker.github.io/blog/an_illustrated_proof_of_the_cap_theoremCool article explaining the problem with saying you can have 2 out of 3 properties of CAPhttp://martin.kleppmann.com/2015/05/11/please-stop-calling-databases-cp-or-ap.htmlMongoDB - https://docs.mongodb.com/manual/introduction/

Tony McGarry, Senior Principal Engineer at Druva, joins W. Curtis Preston and Prasanna Malaiyandi to talk about backing up large, multi-node, sharded NoSQL databases like DynamoDB, Cassandra, and MongoDB.

On episode 5, we do a brief recap of episodes 1 to 4 and solidify the learnings by discussing the NoSQL Document Database and its application in a real-life marketing scenario. Have you ever gotten targeted with images of a product on social media only minutes after you mentioned the product to a friend or browsed it on your phone? Listen more to find out how this works! Relevant timestamps- 0'-1.20'- Recap of 1-4 episodes For the rest of the episode, we discuss a real-life scenario of a consumer being shown images of products on social media that he/she may have browsed only minutes ago. We understand how a NoSQL Document database enables this 'smart marketing'. We chat about ETL (Export, Transfer and Load) Constraints, Formatting Constraints and other constraints that make SQL databases less favorable than NoSQL Databases for the above mentioned application. Reference Video to understand NoSQL Document Database- https://www.youtube.com/watch?v=nigPkP6QeTk

On the third episode of the show, we talk about the different layers of an application and specifically focus on databases. We introduce and breakdown 'SQL' and 'NoSQL' databases. We also talk about their use-cases and benefits while introducing examples like Netflix. We chat about ACID compliance and wrap the episode up, with a quick summary. Recommended reading- A link that summarises SQL v/s NoSQL pretty well- https://www.thorntech.com/2019/03/sql-vs-nosql/ Relevant timestamps:  0:30-2:00-Recap of episode 2 2:00-3:15 Different kinds of layers in an application (Presentation, Application and Database) 3:15-4:00 - Introduction to Databases 4:00- 6:00- SQL 6:00-11:15- NoSQL and types of NoSQL Databases (Netflix Example) 11:15-13:00- Document Databases 13:00- 15:00 Wide column databases 15:00-16:00- Graph Databases 16:00-16:40 - How to decide between SQL and NoSQL Databases 16:40-22:00- ACID Compliance  22:00-24:30- Wrap up and Summary 

Data is sticky and managing it in this new cloud and mobile world is a challenge. The solutions out there vary widely but there are not many that are truly comprehensive.Join Matt Ingenthron, Senior Director of Engineering, to hear about how Couchbase enables data management in this era of digital transformation.  Couchbase has been at the forefront of this transition with their Enterprise Class, Multi-Cloud to Edge NoSQL Database.  Matt will describe how Couchbase improves agility of development, performance of applications and dramatically simplifies management.

In this episode I'm joined by Matt Groves, Senior Developer Advocate at the NoSQL database company, Couchbase. The focus of this episode is to become familiar with NoSQL and where it makes sense to use it in your projects, both new and old. Matt and explore numerous NoSQL database technologies which include Graph, Document, Key-Value, and Columnar, and look at the possible advantages they bring over the RDBMS alternative. I know Matt Groves from my time working with him at Couchbase. While Couchbase will be included in the episode, it is by no means the focus of the episode. A brief writeup to this episode can be found via https://www.thepolyglotdeveloper.com/2018/10/tpdp-e22-nosql-databases-flexibility-non-relational-model/

There was a Cambrian explosion of NoSQL databases just a few short years ago. Each had its own strengths and weaknesses, and none could genuinely call themselves a general purpose enterprise database. DataStax set out to change that. DataStax Enterprise, based on Apache Cassandra, now includes robust search, graph and analytics capabilities, enabling it to support more demanding use cases. In this episode of Pivotal Insights, Jeff and Dormain are honed by Gilbert Lau, Cloud and Big Data Evangelist at DataStax, to discuss the evolution of NoSQL databases.

There was a Cambrian explosion of NoSQL databases just a few short years ago. Each had its own strengths and weaknesses, and none could genuinely call themselves a general purpose enterprise database. DataStax set out to change that. DataStax Enterprise, based on Apache Cassandra, now includes robust search, graph and analytics capabilities, enabling it to support more demanding use cases. In this episode of Pivotal Insights, Jeff and Dormain are honed by Gilbert Lau, Cloud and Big Data Evangelist at DataStax, to discuss the evolution of NoSQL databases.

Learn how the AWS Marketplace brings together customers who have challenges with ISVs who have solutions to those challenges. See how to use relational and NoSQL technologies on AWS to build enterprise and consumer apps. NBC used MarkLogic to deliver an award-winning app that can handle high traffic levels and unexpected usage spikes. NBC’s popular, Emmy-winning, “SNL 40” was launched to celebrate the 40th anniversary of Saturday Night Live, and delivers four decades of sketches and performances. Hosted on AWS, the app — as well as a browser-based platform — are powered by the MarkLogic Enterprise NoSQL database. Come learn from the team who collaborated on this project how to run your own database on AWS, and how to integrate with Amazon RDS and other data stores. A world-recognized automotive brand needed to deliver real-time response about their worldwide fleet vehicles. You will learn how they used a combination of AWS services and FileMaker Cloud, (an Apple subsidiary, procured through AWS Marketplace) to deliver high-scale dealer-facing applications.

In this episode I'm joined by Docker Champion and NoSQL advocate, Arun Gupta where we discuss containers and the relevance and usefulness of them with NoSQL distributed databases. Learn about some of the differences between containers and virtual machines as well as some of the orchestration frameworks available.  You'll walk away with solid information on why you should give Docker and NoSQL a chance within your organization.

In this episode, we discuss this fortnight's interesting big data news that caught our eye and then go on to discuss the basics around authentication in Hadoop for what is the first in a series of episodes that we'll be doing over the next few months on the broad topic of security. 00:00 Recent events Dave: The new science behind customer loyalty http://insights.principa.co.za/the-new-science-behind-customer-loyalty http://insights.principa.co.za/infographic-creating-a-data-driven-customer-loyalty-strategy 5 great charts in 5 lines of R code http://blog.revolutionanalytics.com/2016/08/five-great-charts-in-5-lines-of-r-code-each.html Using big data to create value for customers, not just target them https://hbr.org/2016/08/use-big-data-to-create-value-for-customers-not-just-target-them Jhon: Linux turns 25 (25 August 1991 ) https://www.linux.com/news/linus-torvalds-reflects-25-years-linux http://web.archive.org/web/20100104211620/http://www.linux.org/people/linus_post.html Hadoop 2.7.3 a minor release in the 2.x.y release line, building upon the previous stable release 2.7.2 http://hadoop.apache.org/docs/r2.7.3/ Specification work related to the Hadoop Compatible Filesystem (HCFS) effort. Hadoop in the cloud/as a service getting a lot of attention lately http://hortonworks.com/blog/making-elephant-fly-cloud/ http://blog.cloudera.com/blog/2016/08/analytics-and-bi-on-amazon-s3-with-apache-impala-incubating/ https://vision.cloudera.com/analytic_database_in_cloud/ http://venturebeat.com/2016/08/25/sap-altiscale/ Facebook open sources image-recognition AI with live video in mind https://research.facebook.com/blog/learning-to-segment/ NoSQL Databases: a Survey and Decision Guidance https://medium.baqend.com/nosql-databases-a-survey-and-decision-guidance-ea7823a822d#.c037d5jbj Committer criteria from Apache https://hadoop.apache.org/committer_criteria.html  Maybe they should just have referred to our podcast! :) Episode 11 - Interview with Community Award Winner Venkatesh Sellappa 40:20 Security in Hadoop - Authentication What is Authentication? Why is it important? When should I do it? Hadoop is insecure by default without strong Authentication Kerberos Active Directory, MIT Kerberos and FreeIPA 01:07:49 End Please use the Contact Form on this blog or our twitter feed to send us your questions, or to suggest future episode topics you would like us to cover.

02:34 - Angular in 2015 Visual Studio Code 09:11 - Tooling 10:47 - Angular 2 Courses, Style Guide 13:01 - People Leaving Angular for React ?? 14:31 - No New Frameworks of Consequence in 2016 ?? Cycle.js Elm 21:50 - New Year’s Challenge: Communicate “Why” Pair Programming 25:12 - Opinionated Blog Posts and Rants 28:42 - Mobile Developers and Applications 33:44 - Angular 2 LIVE Predictions Lukas: June 15th John: May 4th (ng-conf) Chuck: mid-July Ward: August Joe: April 1st 39:54 - ES2015/6, ES7 41:15 - Bootstrap Takes a Backseat 41:48 - Inline Styles 43:43 - Containers 44:08 - NOSQL Databases 44:35 - Java 45:06 - Ruby 45:35 - PHP 46:34 - Bootcamps / Coding Camps Education and Job Attainability 54:02 - Revolt on ES6 => Go Back to ES5 ?? 55:49 - WebAssembly Picks Mad Max: Fury Road (Ward) Luca Sestak Duo - Key Engine (Lukas) Star Wars: The Force Awakens (Joe) littleBits (Joe) Submit a CFP for ng-conf! (Joe) Spending time with family (John) Clash of Clans (Chuck) All Remote Confs (Chuck) Swarm Simulator (Chuck) CES (Chuck) The Venetian Hotel (Chuck)

02:34 - Angular in 2015 Visual Studio Code 09:11 - Tooling 10:47 - Angular 2 Courses, Style Guide 13:01 - People Leaving Angular for React ?? 14:31 - No New Frameworks of Consequence in 2016 ?? Cycle.js Elm 21:50 - New Year’s Challenge: Communicate “Why” Pair Programming 25:12 - Opinionated Blog Posts and Rants 28:42 - Mobile Developers and Applications 33:44 - Angular 2 LIVE Predictions Lukas: June 15th John: May 4th (ng-conf) Chuck: mid-July Ward: August Joe: April 1st 39:54 - ES2015/6, ES7 41:15 - Bootstrap Takes a Backseat 41:48 - Inline Styles 43:43 - Containers 44:08 - NOSQL Databases 44:35 - Java 45:06 - Ruby 45:35 - PHP 46:34 - Bootcamps / Coding Camps Education and Job Attainability 54:02 - Revolt on ES6 => Go Back to ES5 ?? 55:49 - WebAssembly Picks Mad Max: Fury Road (Ward) Luca Sestak Duo - Key Engine (Lukas) Star Wars: The Force Awakens (Joe) littleBits (Joe) Submit a CFP for ng-conf! (Joe) Spending time with family (John) Clash of Clans (Chuck) All Remote Confs (Chuck) Swarm Simulator (Chuck) CES (Chuck) The Venetian Hotel (Chuck)

02:34 - Angular in 2015 Visual Studio Code 09:11 - Tooling 10:47 - Angular 2 Courses, Style Guide 13:01 - People Leaving Angular for React ?? 14:31 - No New Frameworks of Consequence in 2016 ?? Cycle.js Elm 21:50 - New Year’s Challenge: Communicate “Why” Pair Programming 25:12 - Opinionated Blog Posts and Rants 28:42 - Mobile Developers and Applications 33:44 - Angular 2 LIVE Predictions Lukas: June 15th John: May 4th (ng-conf) Chuck: mid-July Ward: August Joe: April 1st 39:54 - ES2015/6, ES7 41:15 - Bootstrap Takes a Backseat 41:48 - Inline Styles 43:43 - Containers 44:08 - NOSQL Databases 44:35 - Java 45:06 - Ruby 45:35 - PHP 46:34 - Bootcamps / Coding Camps Education and Job Attainability 54:02 - Revolt on ES6 => Go Back to ES5 ?? 55:49 - WebAssembly Picks Mad Max: Fury Road (Ward) Luca Sestak Duo - Key Engine (Lukas) Star Wars: The Force Awakens (Joe) littleBits (Joe) Submit a CFP for ng-conf! (Joe) Spending time with family (John) Clash of Clans (Chuck) All Remote Confs (Chuck) Swarm Simulator (Chuck) CES (Chuck) The Venetian Hotel (Chuck)

In our second episode (12 minutes long), Alex and Nat talk about the new generation of “NoSQL” databases that have created a lot of interest among web developers; especially those lucky people dealing with thousands of simultaneous users and terabytes of data. Please feel free to leave a comment below after you’ve listened to the episode. [...]