schemaorg VS beekeeper-studio

itemscope itemtype="https://schema.org/Person"> itemprop="name">Scott Nath Work History itemprop="alumniOf" itemscope itemtype="https://schema.org/Organization"> itemprop="name">Company ABC itemprop="description">...company description... itemprop="employee" itemscope itemtype="https://schema.org/EmployeeRole"> itemprop="roleName">Software developer itemprop="description">...details about role... itemprop="alumniOf" itemscope itemtype="https://schema.org/Organization"> itemprop="name">Company Meow itemprop="employee" itemscope itemtype="https://schema.org/EmployeeRole"> itemprop="roleName">Sitting Volunteer History itemprop="alumniOf" itemscope itemtype="https://schema.org/Organization"> itemprop="name">Company 501c3 itemprop="employee" itemscope itemtype="https://schema.org/EmployeeRole"> itemprop="roleName">Software developer for free itemprop="description">...details about role...

I've been re-writing the HTML of my site and added structured data, in the form of microdata attributes, following the Schema.org vocabulary set. Structured data can be understood by search engines and other machines, giving your content structure and context.

Implementing Structured Data Markup annotation system, which can provide additional context about the content to search engines. Structured data markup such as Schema.org can be used to aid search engines to understand the content relevance and significance. This approach can help improve search results by improved ranking and visibility of the content.

export default async function Page({ params }) { const product = await getProduct(params.id); const jsonLd = { "@context": "https://schema.org", "@type": "Product", name: product.name, image: product.image, description: product.description, }; return ( {/* Add JSON-LD to your page */} {/* ... */} section> ); }

const Article = () => { // Dummy article data const article = { title: 'Sample Article Title', description: 'This is a sample article description.', datePublished: '2024-03-23', author: { "@type": "Person", "name": "John Doe" }, image: "https://via.placeholder.com/800x400", publisher: { "@type": "Organization", "name": "Sample News", "logo": { "@type": "ImageObject", "url": "https://via.placeholder.com/200x100" } }, mainEntityOfPage: { "@type": "WebPage", "@id": "https://www.example.com/article" } }; // Define the JsonLd component within the Article component const JsonLd = ({ data }) => ( ); return ( <div> <h1>{article.title}h1> <p>{article.description}p> <p>Date Published: {article.datePublished}p> <p>Author: {article.author.name}p> <img src={article.image} alt={article.title} /> {/* JSON-LD for Article */} <JsonLd data={{ "@context": "https://schema.org", "@type": "NewsArticle", "headline": article.title, "description": article.description, "datePublished": article.datePublished, "author": article.author, "image": [article.image], "publisher": article.publisher, "mainEntityOfPage": article.mainEntityOfPage }} /> div> ); }; export default Article;

itemscope itemtype="http://schema.org/Product"> itemprop="name">Product Name itemprop="description">Product Description itemprop="review" itemscope itemtype="http://schema.org/Review"> itemprop="reviewRating" itemscope itemtype="http://schema.org/Rating"> itemprop="ratingValue">5 stars itemprop="author" itemscope itemtype="http://schema.org/Person"> itemprop="name">Author Name itemprop="datePublished">Date of Review itemprop="reviewBody">Review Body

You can use Schema.org to generate JSON-LD Schema for your website.

It’s also very much still a thing rebranded as Microdata. You can find examples on Schema.org, but now there are easier ways to share the same info; I prefer JSON-LD.

Schema.org provides a shared vocabulary that webmasters can use to mark up their pages in ways that can be understood by major search engines, including Google, Bing, Yahoo!, and Yandex.

If we access a client like PgAdmin or Beekeeper, or accessing its container via bash and checking via CLI, we can see that the table was created successfully:

This tool doesn't let you run SQL queries or create tables. SchemaSpy describes and visualizes an already-created database.

To work directly with SQL, I recommend https://www.beekeeperstudio.io/ or https://dbgate.org/

I use the free “community” edition daily: https://github.com/beekeeper-studio/beekeeper-studio/release...

postgres has some cool tools these days. postico if you are on macos or my personal fav lately has been https://www.beekeeperstudio.io/

Beekeeper Studio is a modern (aesthetic) and lightweight SQL client that supports MySQL, Postgres, SQLite, SQL Server, etc. It is available on Linux, Mac and Windows.

I'm trying to renew my certificate for Beekeeper Studio, 3 years ago it was a simple download, but now it costs 3x the price and they want to ship me a physical device with the private key on it.

`cask "beekeeper-studio"` [link][oss] for anything database