Software Alternatives, Accelerators & Startups

Oracle Data Access Components VS bokeh python

Compare Oracle Data Access Components VS bokeh python and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Oracle Data Access Components logo Oracle Data Access Components

Enjoy the highest performance and unlimited possibilities when working with Oracle

bokeh python logo bokeh python

This Python tutorial will get you up and running with Bokeh, using examples and a real-world dataset. You'll learn how to visualize your data, customize and organize your visualizations, and add interactivity.
  • Oracle Data Access Components Landing page
    Landing page //
    2023-04-07

Oracle Data Access Components (ODAC) is a library of components that provides native connectivity to Oracle from Delphi and C++Builder including Community Edition, as well as Lazarus (and Free Pascal) on Windows, Linux, macOS, iOS, and Android for both 32-bit and 64-bit platforms. The ODAC library is designed to help programmers develop faster and more native Oracle database applications.

ODAC, a high-performance and feature-rich Oracle connectivity solution, is an efficient native alternative to the Borland Database Engine (BDE) and standard dbExpress driver. It provides both possibilities of connection to Oracle through native Oracle data access and direct Oracle access from Delphi without Oracle Client.

  • bokeh python Landing page
    Landing page //
    2023-08-18

Oracle Data Access Components features and specs

  • Direct access to server data. Does not require installation of other data provider layers (such as BDE and ODBC)
  • Interface compatible with standard data access methods, such as BDE and ADO
  • VCL, LCL and FMX versions of library available
  • Separated run-time and GUI specific parts allow you to create pure console applications such as CGI
  • Unicode and national charset support
  • Highly usable design time support
  • Easy to deploy

bokeh python features and specs

  • Interactivity
    Bokeh provides interactive plots and dashboards that can enhance the user experience by allowing them to explore data by zooming, panning, and hovering.
  • Web Integration
    It generates outputs that are readily usable in web applications. Bokeh plots can be embedded in web pages, making it suitable for creating dashboards and web-based data visualization applications.
  • Versatility
    Bokeh supports a wide variety of plots and chart types, which allows users to create complex and informative visualizations.
  • Pythonic Syntax
    The library has an API that is intuitive for Python users, making it easier to learn and integrate into Python-based projects.
  • Server for Real-time Updates
    Bokeh server allows for the creation of interactive, real-time streaming web applications, which is useful for applications requiring live data updates.

Possible disadvantages of bokeh python

  • Learning Curve
    Despite its intuitive syntax, Bokeh's extensive capabilities and features can present a steeper learning curve, particularly for beginners in data visualization.
  • Rendering Performance
    For very large datasets, Bokeh might encounter performance issues, such as slower rendering times in the browser compared to other digital visualization technologies.
  • Limited 3D Capabilities
    Unlike some other visualization libraries, Bokehโ€™s support for 3D plotting is limited, which might be a constraint for users needing advanced 3D plotting features.
  • Complexity with Advanced Plots
    While Bokeh is great for basic plots, creating highly customized or advanced visualizations may require more effort, with users potentially needing to write custom JavaScript callbacks.
  • Dependencies
    Bokehโ€™s reliance on JavaScript and other underlying libraries might pose challenges in environments where managing dependencies is complex.

Oracle Data Access Components videos

How to Connect Devart ODAC to Oracle Database: Step-by-Step Tutorial

bokeh python videos

No bokeh python videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Oracle Data Access Components and bokeh python)
Monitoring Tools
100 100%
0% 0
Development Tools
0 0%
100% 100
Diagnostics Software
100 100%
0% 0
Data Science And Machine Learning

User comments

Share your experience with using Oracle Data Access Components and bokeh python. For example, how are they different and which one is better?
Log in or Post with

What are some alternatives?

When comparing Oracle Data Access Components and bokeh python, you can also consider the following products

Universal Data Access Components - Enterprise solution at a low price. Powerful functionality with fast and reliable support

Ionic - Ionic is a cross-platform mobile development stack for building performant apps on all platforms with open web technologies.

MxToolBox - All of your MX record, DNS, blacklist and SMTP diagnostics in one integrated tool.

python xlrd - Please use openpyxl where you can... Contribute to python-excel/xlrd development by creating an account on GitHub.

SQL Server Data Access Components - Enjoy the highest performance and unlimited possibilities when working with SQL Server

python wiki - Component Libraries