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Apache Kafka VS ParseHub

Compare Apache Kafka VS ParseHub and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Apache Kafka logo Apache Kafka

Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.

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 Kafka Landing page
    Landing page //
    2022-10-01
  • ParseHub Landing page
    Landing page //
    2021-09-12

Apache Kafka features and specs

  • High Throughput
    Kafka is capable of handling thousands of messages per second due to its distributed architecture, making it suitable for applications that require high throughput.
  • Scalability
    Kafka can easily scale horizontally by adding more brokers to a cluster, making it highly scalable to serve increased loads.
  • Fault Tolerance
    Kafka has built-in replication, ensuring that data is replicated across multiple brokers, providing fault tolerance and high availability.
  • Durability
    Kafka ensures data durability by writing data to disk, which can be replicated to other nodes, ensuring data is not lost even if a broker fails.
  • Real-time Processing
    Kafka supports real-time data streaming, enabling applications to process and react to data as it arrives.
  • Decoupling of Systems
    Kafka acts as a buffer and decouples the production and consumption of messages, allowing independent scaling and management of producers and consumers.
  • Wide Ecosystem
    The Kafka ecosystem includes various tools and connectors such as Kafka Streams, Kafka Connect, and KSQL, which enrich the functionality of Kafka.
  • Strong Community Support
    Kafka has strong community support and extensive documentation, making it easier for developers to find help and resources.

Possible disadvantages of Apache Kafka

  • Complex Setup and Management
    Kafka's distributed nature can make initial setup and ongoing management complex, requiring expert knowledge and significant administrative effort.
  • Operational Overhead
    Running Kafka clusters involves additional operational overhead, including hardware provisioning, monitoring, tuning, and scaling.
  • Latency Sensitivity
    Despite its high throughput, Kafka may experience increased latency in certain scenarios, especially when configured for high durability and consistency.
  • Learning Curve
    The concepts and architecture of Kafka can be difficult for new users to grasp, leading to a steep learning curve.
  • Hardware Intensive
    Kafka's performance characteristics often require dedicated and powerful hardware, which can be costly to procure and maintain.
  • Dependency Management
    Managing Kafka's dependencies and ensuring compatibility between versions of Kafka, Zookeeper, and other ecosystem tools can be challenging.
  • Limited Support for Small Messages
    Kafka is optimized for large throughput and can be inefficient for applications that require handling a lot of small messages, where overhead can become significant.
  • Operational Complexity for Small Teams
    Smaller teams might find the operational complexity and maintenance burden of Kafka difficult to manage without a dedicated operations or DevOps team.

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.

Apache Kafka videos

+ Add

Apache Kafka Tutorial | What is Apache Kafka? | Kafka Tutorial for Beginners | Edureka

More videos:

  • Review - Apache Kafka - Getting Started - Kafka Multi-node Cluster - Review Properties
  • Review - 4. Apache Kafka Fundamentals | Confluent Fundamentals for Apache Kafka®
  • Review - Apache Kafka in 6 minutes
  • Review - Apache Kafka Explained (Comprehensive Overview)
  • Review - 2. Motivations and Customer Use Cases | Apache Kafka Fundamentals

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 Kafka and ParseHub)

Apache Kafka

ParseHub

Stream Processing
100 100%
Stream Processing
0% 0
Web Scraping
0 0%
Web Scraping
100% 100
Data Integration
100 100%
Data Integration
0% 0
Data Extraction
0 0%
Data Extraction
100% 100

User comments

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Reviews

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

Apache Kafka Reviews

Best ETL Tools: A Curated List
Debezium is an open-source Change Data Capture (CDC) tool that originated from RedHat. It leverages Apache Kafka and Kafka Connect to enable real-time data replication from databases. Debezium was partly inspired by Martin Kleppmann’s "Turning the Database Inside Out" concept, which emphasized the power of the CDC for modern data pipelines.
Source: estuary.dev
Best message queue for cloud-native apps
If you take the time to sort out the history of message queues, you will find a very interesting phenomenon. Most of the currently popular message queues were born around 2010. For example, Apache Kafka was born at LinkedIn in 2010, Derek Collison developed Nats in 2010, and Apache Pulsar was born at Yahoo in 2012. What is the reason for this?
Source: docs.vanus.ai
Are Free, Open-Source Message Queues Right For You?
Apache Kafka is a highly scalable and robust messaging queue system designed by LinkedIn and donated to the Apache Software Foundation. It's ideal for real-time data streaming and processing, providing high throughput for publishing and subscribing to records or messages. Kafka is typically used in scenarios that require real-time analytics and monitoring, IoT applications,...
Source: blog.iron.io
10 Best Open Source ETL Tools for Data Integration
It is difficult to anticipate the exact demand for open-source tools in 2023 because it depends on various factors and emerging trends. However, open-source solutions such as Kubernetes for container orchestration, TensorFlow for machine learning, Apache Kafka for real-time data streaming, and Prometheus for monitoring and observability are expected to grow in prominence in...
Source: testsigma.com
11 Best FREE Open-Source ETL Tools in 2024
Apache Kafka is an Open-Source Data Streaming Tool written in Scala and Java. It publishes and subscribes to a stream of records in a fault-tolerant manner and provides a unified, high-throughput, and low-latency platform to manage data.
Source: hevodata.com

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, Apache Kafka seems to be a lot more popular than ParseHub. While we know about 144 links to Apache Kafka, we've tracked only 3 mentions of ParseHub. 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 Kafka mentions (144)

View more

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 3 years ago
  • Free for dev - list of software (SaaS, PaaS, IaaS, etc.)
    Parsehub.com — Extract data from dynamic sites, turn dynamic websites into APIs, 5 projects free. - Source: dev.to / almost 4 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 / about 4 years ago

What are some alternatives?

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

RabbitMQ - RabbitMQ is an open source message broker software.

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.

StatCounter - StatCounter is a simple but powerful real-time web analytics service that helps you track, analyse and understand your visitors so you can make good decisions to become more successful online.

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

Apache ActiveMQ - Apache ActiveMQ is an open source messaging and integration patterns server.

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

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