May 2021 Summaries

Memgraph 1.5 introduces significant updates and new features to enhance its database capabilities. Notably, the release includes database triggers, allowing users to automate actions when nodes or edges are created, deleted, or updated, thereby offering more control over database events. Replication, previously exclusive to the Enterprise version, is now available in the Community version, enabling seamless data synchronization across instances for high availability. The update also provides tools to manage memory usage effectively, such as setting memory limits and freeing unused memory. Users can now organize foreign modules across multiple directories, promoting better abstraction and modularity. Additionally, Memgraph now supports loading CSV files directly during queries with the LOAD CSV clause, eliminating the need for database downtime during imports. The mgconsole command line interface replaces mg_client, offering a more robust environment for running queries on Windows and macOS. These enhancements aim to provide users with greater flexibility, control, and ease of use in managing and querying graph data.

Memgraph participated in the Microsoft Build 2021 conference, held in a digital format on May 25 and 26, where it showcased its cutting-edge developer solutions as part of Microsoft's in-program startups. The virtual booth featured engaging content, including a video demonstration of using graph analytics to explore relationships among Game of Thrones characters and an interview with the Solutions team discussing graph analytics applications. Attendees were also invited to read a free ebook on the power and applicability of graph analytics. Alongside Memgraph, other startups featured included Prefect, a workflow management system; Split, a feature delivery platform; LottieFiles, an animation workflow platform; and Moveworks, an AI-driven help desk automation company. The conference was open to all, free of charge, encouraging widespread participation.

In the exploration of the Eurovision Song Contest through graph analytics, the article delves into the intricate relationships and voting patterns shaped by geopolitical factors, neighborhood affinities, and cultural ties. Utilizing a dataset containing country nodes and voting edges, it analyzes how strategic voting, neighbor preferences, and political rivalries influence the contest's outcomes. The piece highlights Ireland and Sweden's consistent victories and the UK's frequent runner-up status, while also examining how countries allocate points based on jury votes and public televoting. Memgraph Lab is employed to visualize these data patterns, revealing that neighboring countries often exchange the most points, significantly impacting results. The analysis uncovers that countries with more neighbors, like France, Russia, and Germany, often have an edge in accumulating votes, suggesting that geographical proximity plays a crucial role in the contest's dynamics. Through these insights, the article invites readers to consider whether winning Eurovision is merely about having a catchy song or if deeper political and social connections are at play.

Memgraph participated in the RockPaperStartups 2021 conference, an event organized by Netokracija that brought together startup founders and executives from Croatia to discuss the future of startups and the development of the startup ecosystem. The conference highlighted the dynamic nature of the local startup scene, showcasing recent notable events such as significant investment rounds and acquisitions involving companies like Photomath and Infobip. Memgraph's CEO and co-founder, Dominik Tomičević, was featured on a panel discussing topics such as product development, funding, and the future of startups, alongside leaders from CircuitMess, Airt, and Robotiq. The conference encouraged online participation and offered a chance to learn about Memgraph's history and future plans, with recordings available for those unable to attend live.

The tutorial provides a detailed guide on building a BitClout social network visualization app using Memgraph, Python, and D3.js. BitClout is a decentralized social network built on its custom blockchain, allowing users to speculate on the value of people and posts. The tutorial explains how to utilize Docker for containerization to facilitate cross-platform development, and how to scrape BitClout data using Python tools like Selenium and Beautiful Soup. It details the creation of a Flask server backend to visualize the BitClout network, including setting up the server, populating the database with CSV data, and handling HTTP requests. The frontend is constructed using D3.js, with a focus on choosing between canvas and SVG for rendering, and implementing drag and zoom functionalities for interactive visualization. The tutorial concludes by demonstrating how to Dockerize the application and provides steps to launch the app, emphasizing the role of Memgraph in handling streaming data and building sophisticated models for real-time querying.

BitClout is a novel social network built on its own blockchain, allowing users to speculate on the value of people and posts with real money, similar to Bitcoin's architecture but with enhanced social network capabilities. Since its inception in March 2021, it has attracted significant investment, with users aiming to profit by identifying undervalued content creators based on the number of supporters, known as HODLers, holding their coins. The platform's community can be represented as a graph, where nodes are content creators and investors, and edges denote their connections. Utilizing algorithms like Google's PageRank and the Louvain method, users can predict which connections will form next, potentially yielding profits. The PageRank algorithm ranks creators based on the quantity of connections, while the Louvain method detects community clusters. To acquire data on HODLers, a Python script was created to scrape BitClout accounts, and the data was analyzed using Memgraph, a graph analytics platform, due to its efficiency over Python's networkx library. The data was then visualized using various tools, including MemgraphLab, D3.js, and ObservableHQ, highlighting the challenges of data presentation despite straightforward analysis.

The text explores the code assignment problem in telecommunication networks, focusing on how to optimize network performance and prevent call drops using graph algorithms and Memgraph MAGE. It explains the challenges of ensuring quality connections between phones and base stations, emphasizing the importance of distinct coding to avoid signal interference. The article describes how telecommunication networks can be modeled as graphs, with nodes representing base stations and edges indicating potential signal interference. It presents the graph coloring problem as a solution, where different "colors" (codes) are assigned to nodes to minimize interference. Memgraph and its extension MAGE are used to implement this solution, leveraging graph algorithms to optimize code planning. The article also provides a practical guide on visualizing and solving the problem using Memgraph Lab, detailing the steps to execute the graph coloring algorithm and interpret results. Additionally, it touches on quantum annealing as a metaheuristic approach to solving optimization problems, highlighting its potential to find "sufficiently good" solutions rapidly, even if not perfect. The tutorial concludes by encouraging the exploration of other algorithms within the MAGE library and invites contributions to the MAGE repository.