Netlify, a platform for modern web development, announced Netlify Edge Functions, bringing standards-based edge compute to Netlify’s development workflow. Developers can now build fast web experiences in less time, using Edge Functions to run dynamic content or even an entire application from the network edge without compromising performance. Built on Deno, an open source runtime, Edge Functions work out-of-the-box with new server-side features from existing web frameworks like Next.js, Nuxt, Astro, Eleventy, and SvelteKit as well as new edge-first frameworks like Hydrogen and Remix.
The recent macrotrend of edge computing has led to a wave of innovation at the network edge, but many of these new solutions are proprietary, don’t use popular programming languages, and don’t offer integrations with multiple web frameworks. As a result, edge compute has added substantial complexity to the software development lifecycle. Netlify Edge Functions were built to be an antidote, letting development teams avoid this tradeoff and, ultimately, deliver modern web experiences to market much faster.
Netlify’s suite of serverless capabilities – Netlify Functions, Background Functions, Scheduled Functions, and now Edge Functions – give developers the flexibility to apply compute where and when they need it. Netlify Edge Functions is now available in public beta.
Element, a software provider in IT/OT data management for industrial companies, announced new functionality for simplified connections, knowledge graph-based modeling, and advanced joins. Together they increase flexibility and speed up model development for organizations seeking to deploy digital twins or pursue industrial transformation.
The Connector Portal provides access to pre-built connectors for a range of commonly-used data sources and consuming targets, speeding analytics projects by reducing manually establishing connections. The portal also provides a connector framework that developers can use to build their own custom connectors.
Unify Graph brings a knowledge graph approach to bear for mapping the complex data environments typical at most enterprises that data teams must operate across. It allows flexible data modeling spanning arbitrary dimensions such as processes, assets, organizations necessary for building effective digital twins. The graphs can be queried and explored within Unify or exported for consumption by graph database products such as AWS Neptune or Neo4j.
The Advanced Joins functionality enables users to combine data from various sources based on matching multiple relevant data fields and using matching approaches. The fuzzy matching approach is configurable and allows the user to specify a similarity threshold for deciding matches.