JDBI VS Plotly
Compare JDBI VS Plotly and see what are their differences
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JDBI
Javalin
Micronaut Framework
Hibernate
Prisma GraphQL API
Postgres.js
Hibernate ORM
Hasura
Plotly
D3.js
RAWGraphs
Tableau
Google Charts
Highcharts
Bokeh
Chart.js
Plotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.
Plotly might be a bit more popular than JDBI. We know about 34 links to it since March 2021 and only 26 links to JDBI. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Directly using the JDBC API in your application code is low-level and verbose. That's why libraries like Jdbi, Spring JDBC Template And Sql2o exist. They provide: named parameters, row mapping, pluggable data type binders/ row mappers/ JSON mappers. - Source: dev.to / 6 months ago
Suppose we're developing an application that allows speakers to submit their talks to a conference (for simplicity, we'll only record the talk's title). Following the Transaction Script pattern, the method for submitting a talk might look like this (using JDBI for SQL):. - Source: dev.to / over 1 year ago
_relational_ is the key word you're missing. ORMs map _objects_ to _relations_ (i.e. tables). "Unlike ORM frameworks, MyBatis does not map Java objects to database tables but Java methods to SQL statements." https://en.wikipedia.org/wiki/MyBatis "Jdbi is not an ORM. It is a convenience library to make Java database operations simpler and more pleasant to program than raw JDBC." https://jdbi.org/ "While jOOQ is not... - Source: Hacker News / almost 2 years ago
While this may work for greenfield applications, I don't see this working well for preexisting schemas. From their getting started page: "Database fields are automatically created for any abstract getter methods", which definitely scares me away since they seem to be relying on automatic field type conversions. I prefer to manage my schemas when I can and do type and DAO conversions via mapper classes in the very... - Source: Hacker News / almost 3 years ago
Someone else mentioned jOOQ, but personally I also rather enjoyed JDBI3: https://jdbi.org/#_introduction_to_jdbi_3 It addresses the issues with using JDBC directly (not nice ergonomics), while still letting you work with SQL directly without too many abstractions in the middle. In combination with Dropwizard, it was pretty pleasant: https://www.dropwizard.io/en/stable/manual/jdbi3.html Other than that, I actually... - Source: Hacker News / almost 3 years ago
Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 6 months ago
Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / almost 2 years ago
How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago
Javalin - Simple REST APIs for Java and Kotlin
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
Micronaut Framework - Build modular easily testable microservice & serverless apps
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...
Hibernate - Hibernate an open source Java persistence framework project.
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.