Software Alternatives, Accelerators & Startups
Register | Login

Apache Ambari VS ParseHub

Compare Apache Ambari VS ParseHub and see what are their differences

9Proxy
Clean. Fast. Premium Residential Proxies, Starting from $0.015/IP and $0.68/GB. featured
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.
Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Apache Ambari logo Apache Ambari

Ambari is aimed at making Hadoop management simpler by developing software for provisioning, managing, and monitoring Hadoop clusters.

ParseHub logo ParseHub

ParseHub is a free web scraping tool. With our advanced web scraper, extracting data is as easy as clicking the data you need.
  • Apache Ambari Landing page
    Landing page //
    2023-01-08
  • ParseHub Landing page
    Landing page //
    2021-09-12

Apache Ambari features and specs

  • Centralized Management
    Apache Ambari provides a centralized platform to manage, monitor, and provision Hadoop clusters efficiently. This feature simplifies the administration tasks by offering a single interface for managing cluster operations.
  • User-Friendly Interface
    Ambari offers a graphical user interface (GUI) that is intuitive and easy to use, enabling administrators to manage clusters without requiring extensive command-line knowledge.
  • Automated Installation
    It supports automated installation and configuration of Hadoop components, reducing the complexity and time required to set up a cluster.
  • Real-time Monitoring
    Ambari provides real-time insights into cluster health and performance through a variety of metrics and dashboards, allowing for proactive management.
  • Extensibility
    The platform is designed to be extensible, allowing developers to write custom alerts and metrics, thus adapting the system to meet specific needs.

Possible disadvantages of Apache Ambari

  • Resource Intensive
    Ambari can consume significant system resources, especially in larger clusters, which could impact performance if resources are not adequately provisioned.
  • Limited Support for Non-Hadoop Ecosystems
    The primary focus of Apache Ambari is on Hadoop ecosystems, and it lacks extensive support for non-Hadoop big data technologies, which can limit its applicability in heterogeneous environments.
  • Complexity for Small Clusters
    For smaller Hadoop deployments, the use of Ambari might be overkill and add unnecessary complexity due to its comprehensive nature.
  • Dependency on Updates
    Users can encounter compatibility issues or bugs following updates, which can require troubleshooting and delay important operations.
  • Steep Learning Curve for Customization
    While it is extensible, customization in Ambari can have a steep learning curve, demanding deeper technical knowledge to implement specific configurations or custom components.

ParseHub features and specs

  • User-friendly Interface
    ParseHub offers a point-and-click interface that makes it easy for users to extract data from websites without needing any coding skills.
  • Advanced Features
    The tool supports complex data extraction tasks, including handling AJAX, JavaScript, infinite scroll, forms, and CAPTCHA.
  • Cross-platform Compatibility
    ParseHub is available as a web app and a desktop application, making it accessible on multiple operating systems.
  • API Integration
    ParseHub provides an API that allows for easy integration with other applications, enabling automated data extraction workflows.
  • Schedule and Automate
    Users can schedule their data extraction tasks to run at specific intervals, which is useful for keeping datasets up-to-date.
  • Cloud Storage
    Extracted data is stored in the cloud, allowing easy access and management of large datasets without consuming local storage resources.
  • Free Tier
    ParseHub offers a free tier that allows users to perform a limited number of data extraction tasks, suitable for small projects or initial testing.

Possible disadvantages of ParseHub

  • Learning Curve for Complex Tasks
    While the basic interface is user-friendly, advanced data extraction tasks may require a steep learning curve to master.
  • Monthly Limits
    The free tier and lower-tier plans have limits on the number of tasks and the amount of data that can be extracted per month, which could constrain heavy users.
  • Pricing
    Higher-tier plans can become expensive, especially for businesses that require extensive data extraction capabilities.
  • Performance Issues
    Users have reported occasional performance issues and bugs when dealing with very large or complex websites, which can affect the reliability of the data extraction processes.
  • Limited Export Formats
    While ParseHub supports common formats like CSV, JSON, and Excel, it lacks support for some specialized or less common file formats.
  • Customer Support
    Some users have reported that customer support can be slow to respond to issues, which could be problematic for time-sensitive projects.
  • Privacy Concerns
    Since the data extraction occurs on ParseHub's servers, there could be privacy concerns related to the handling of sensitive or proprietary data.

Analysis of ParseHub

Overall verdict

  • ParseHub is generally a reliable and effective tool for web scraping purposes. Its ease of use and powerful features make it a strong choice for both beginners and experienced data analysts. However, users should be aware of potential limitations regarding speed and handling extremely large-scale data scraping tasks.

Why this product is good

  • ParseHub is considered a good tool due to its versatility in web scraping without requiring extensive programming knowledge. It provides a user-friendly interface that allows users to automate data extraction tasks from websites. Additionally, it supports complex website structures and can handle dynamic content and JavaScript-driven sites.

Recommended for

    ParseHub is recommended for business analysts, data scientists, researchers, and anyone who needs to extract data from websites regularly but does not wish to dive deeply into coding. It's also a good option for individuals or small businesses looking to gather market research, product pricing information, or other competitive intelligence from web sources.

Apache Ambari videos

No Apache Ambari videos yet. You could help us improve this page by suggesting one.

Add video

ParseHub videos

+ Add

ParseHub Tutorial: Scrape Ratings and Reviews from a Website

More videos:

  • Tutorial - ParseHub Tutorial: Scraping Product Details from Amazon

Category Popularity

0-100% (relative to Apache Ambari and ParseHub)

Apache Ambari

ParseHub

Development
100 100%
Development
0% 0
Web Scraping
0 0%
Web Scraping
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Data Extraction
0 0%
Data Extraction
100% 100

User comments

Share your experience with using Apache Ambari and ParseHub. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Ambari and ParseHub

Apache Ambari Reviews

We have no reviews of Apache Ambari yet.
Be the first one to post

ParseHub Reviews

Best Data Scraping Tools
Parsehub is a fantastic tool for people who want to extract data from websites without coding. It is used widely by data analysts, journalists, data scientists, and many fields. Parse Hub is easier to use; you can click on the data that you are working on to build a web scraper, which then exports the data in excel format or JSON.
Source: pamelaewallaceu.medium.com

Social recommendations and mentions

Based on our record, ParseHub should be more popular than Apache Ambari. It has been mentiond 3 times since March 2021. 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.

Apache Ambari mentions (1)

  • In One Minute : Hadoop
    Ambari, A web-based tool for provisioning, managing, and monitoring Apache Hadoop clusters which includes support for Hadoop HDFS, Hadoop MapReduce, Hive, HCatalog, HBase, ZooKeeper, Oozie, Pig and Sqoop. Ambari also provides a dashboard for viewing cluster health such as heatmaps and ability to view MapReduce, Pig and Hive applications visually along with features to diagnose their performance characteristics in... - Source: dev.to / over 3 years ago

ParseHub mentions (3)

  • Home Depot price data using IMPORTXML?
    I've heard some folks have success with "parsehub.com", though I once tried it for a project and found it a bit intimidating... Source: over 4 years ago
  • Free for dev - list of software (SaaS, PaaS, IaaS, etc.)
    Parsehub.com โ€” Extract data from dynamic sites, turn dynamic websites into APIs, 5 projects free. - Source: dev.to / about 5 years ago
  • Turn any website into an API with no code
    Parsehub is a powerful web scraping GUI tool for efficient fetching and manipulating data from any webpage. It helps you create an API output for a given website. You can even sanitize your content by using regex or replace function. So the input is a URL and the output is a structured json file. - Source: dev.to / over 5 years ago

What are some alternatives?

When comparing Apache Ambari and ParseHub, you can also consider the following products

Apache HBase - Apache HBase โ€“ Apache HBaseโ„ข Home

import.io - Import. io helps its users find the internet data they need, organize and store it, and transform it into a format that provides them with the context they need.

Apache Pig - Pig is a high-level platform for creating MapReduce programs used with Hadoop.

Apify - Apify is a web scraping and automation platform that can turn any website into an API.

Apache Mahout - Distributed Linear Algebra

Octoparse - Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.

Loading...