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Apache Spark VS Octoparse

Compare Apache Spark VS Octoparse and see what are their differences

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Apache Spark logo Apache Spark

Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Octoparse logo Octoparse

Octoparse provides easy web scraping for anyone. Our advanced web crawler, allows users to turn web pages into structured spreadsheets within clicks.
  • Apache Spark Landing page
    Landing page //
    2021-12-31
  • Octoparse Landing page
    Landing page //
    2023-09-09

Extract web data in 3 steps

  1. Enter website URL you'd like to extract data from
  2. Click on the target data to extract
  3. Run the extraction and get data

Apache Spark features and specs

  • Speed
    Apache Spark processes data in-memory, significantly increasing the processing speed of data tasks compared to traditional disk-based engines.
  • Ease of Use
    Spark offers high-level APIs in Java, Scala, Python, and R, making it accessible to a broad range of developers and data scientists.
  • Advanced Analytics
    Spark supports advanced analytics, including machine learning, graph processing, and real-time streaming, which can be executed in the same application.
  • Scalability
    Spark can handle both small- and large-scale data processing tasks, scaling seamlessly from a single machine to thousands of servers.
  • Support for Various Data Sources
    Spark can integrate with a wide variety of data sources, including HDFS, Apache HBase, Apache Hive, Cassandra, and many others.
  • Active Community
    Spark has a vibrant and active community, providing a wealth of extensions, tools, and support options.

Possible disadvantages of Apache Spark

  • Memory Consumption
    Spark's in-memory processing can be resource-intensive, requiring substantial amounts of RAM, which can drive up costs for large-scale deployments.
  • Complexity in Configuration
    To optimize performance, Spark requires careful configuration and tuning, which can be complex and time-consuming.
  • Learning Curve
    Despite its ease of use, mastering the full range of Spark's features and best practices can take considerable time and effort.
  • Latency for Small Data
    For smaller datasets or low-latency requirements, Spark might not be the most efficient choice, as other technologies could offer better performance.
  • Integration Overhead
    Though Spark integrates with many systems, incorporating it into an existing data infrastructure can introduce additional overhead and complexity.
  • Community Support Variability
    While the community is active, the support and quality of third-party libraries and tools can be inconsistent, leading to potential challenges in implementation.

Octoparse features and specs

  • User-Friendly Interface
    Octoparse offers a drag-and-drop interface, which makes it accessible even for users without any coding experience. This lowers the learning curve significantly.
  • Customizable Workflows
    The tool provides various options for customizing data extraction workflows, allowing users to tailor the extraction process according to their specific needs.
  • Cloud-Based Platform
    Octoparse runs in the cloud, enabling users to execute and schedule scraping tasks without the need for local resources, thus saving time and computational power.
  • Automatic IP Rotation
    Automatic IP rotation helps to prevent IP bans and CAPTCHAs, making the scraping process more efficient and reducing the risk of getting blocked by websites.
  • Data Export Options
    The platform offers various data export options, such as CSV, Excel, HTML, and JSON. It can also directly integrate with databases and APIs for seamless data transfer.

Possible disadvantages of Octoparse

  • Pricing
    While Octoparse offers a free plan, the advanced features and higher extraction limits are only available in the paid plans, which can be expensive for individual users and small businesses.
  • Learning Curve for Advanced Features
    Despite its user-friendly interface, mastering Octoparse's advanced features and capabilities can still require a steep learning curve for some users.
  • Performance Issues
    Some users have reported occasional performance issues, such as crashes and slowdowns, particularly with larger data extraction tasks.
  • Data Accuracy
    In some instances, the extracted data may have accuracy issues, requiring manual verification and cleaning, which can be time-consuming.
  • Limited Customer Support
    Customer support can be limited, especially for users on the free or lower-tier plans, making it difficult to resolve complex issues promptly.

Analysis of Apache Spark

Overall verdict

  • Yes, Apache Spark is generally considered good, especially for organizations and individuals that require efficient and fast data processing capabilities. It is well-supported, frequently updated, and widely adopted in the industry, making it a reliable choice for big data solutions.

Why this product is good

  • Apache Spark is highly valued because it provides a fast and general-purpose cluster-computing framework for big data processing. It offers extensive libraries for SQL, streaming, machine learning, and graph processing, making it versatile for various data processing needs. Its in-memory computing capability boosts the processing speed significantly compared to traditional disk-based processing. Additionally, Spark integrates well with Hadoop and other big data tools, providing a seamless ecosystem for large-scale data analysis.

Recommended for

  • Data scientists and engineers working with large datasets.
  • Organizations leveraging machine learning and analytics for decision-making.
  • Businesses needing real-time data processing capabilities.
  • Developers looking to integrate with Hadoop ecosystems.
  • Teams requiring robust support for multiple data sources and formats.

Analysis of Octoparse

Overall verdict

  • Octoparse is generally considered a good tool for web scraping, particularly for those who want to extract data without deep technical knowledge. Its ease of use, combined with advanced features, make it a strong choice for users across different sectors. However, restrictions on the free version and occasional complexity in dealing with dynamic websites may require consideration.

Why this product is good

  • Octoparse is a powerful web scraping tool that is especially good for non-programmers due to its user-friendly interface. It offers features like point-and-click UI, pre-set scraping templates, cloud-based data extraction, scheduling, and API access. These features make it accessible for users who need to collect and analyze web data without writing code and ensure it can handle a variety of tasks from market research to competitive analysis.

Recommended for

    Small to medium-sized businesses, marketing professionals, data analysts, researchers, and anyone needing to automate data extraction tasks without investing heavily in technical resources or hiring developers.

Apache Spark videos

+ Add

Weekly Apache Spark live Code Review -- look at StringIndexer multi-col (Scala) & Python testing

More videos:

  • Review - What's New in Apache Spark 3.0.0
  • Review - Apache Spark for Data Engineering and Analysis - Overview

Octoparse videos

+ Add

Create your first scraper with Octoparse 7 X

More videos:

  • Review - Web Scraping Amazon Products with Octoparse - Basics (PSC5)

Category Popularity

0-100% (relative to Apache Spark and Octoparse)

Apache Spark

Octoparse

Databases
100 100%
Databases
0% 0
Web Scraping
0 0%
Web Scraping
100% 100
Big Data
100 100%
Big Data
0% 0
Data Extraction
0 0%
Data Extraction
100% 100

User comments

Share your experience with using Apache Spark and Octoparse. For example, how are they different and which one is better?
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Reviews

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

Apache Spark Reviews

15 data science tools to consider using in 2021
Apache Spark is an open source data processing and analytics engine that can handle large amounts of data -- upward of several petabytes, according to proponents. Spark's ability to rapidly process data has fueled significant growth in the use of the platform since it was created in 2009, helping to make the Spark project one of the largest open source communities among big...
Source: searchbusinessanalytics.techtarget.com
Top 15 Kafka Alternatives Popular In 2021
Apache Spark is a well-known, general-purpose, open-source analytics engine for large-scale, core data processing. It is known for its high-performance quality for data processing – batch and streaming with the help of its DAG scheduler, query optimizer, and engine. Data streams are processed in real-time and hence it is quite fast and efficient. Its machine learning...
Source: www.spec-india.com
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Spark is an open-source and flexible in-memory framework which serves as an alternative to map-reduce for handling batch, real-time analytics and data processing workloads. It provides native bindings for the Java, Scala, Python, and R programming languages, and supports SQL, streaming data, machine learning and graph processing. From its beginning in the AMPLab at...
Source: www.analyticsinsight.net

Octoparse Reviews

  1. Christina
    I want to give this prodect a huge shout-out! It really works like a charm!

    I've been playing around with different scraping tools in the past month, trying to find the best one to help with my research project, and I have to say this new feature of auto-detection comes like a life-savor. I only need to give the software the link and it will auto-detect the content and build the crawler for me. I can even enjoy it with just a free plan!

Social recommendations and mentions

Based on our record, Apache Spark seems to be a lot more popular than Octoparse. While we know about 70 links to Apache Spark, we've tracked only 3 mentions of Octoparse. 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 Spark mentions (70)

  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave â€” can read and/or write Iceberg data directly. - Source: dev.to / about 2 months ago
  • How to Reduce Big Data Analytics Costs by 90% with Karpenter and Spark
    Apache Spark powers large-scale data analytics and machine learning, but as workloads grow exponentially, traditional static resource allocation leads to 30–50% resource waste due to idle Executors and suboptimal instance selection. - Source: dev.to / about 2 months ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / 3 months ago
  • The Application of Java Programming In Data Analysis and Artificial Intelligence
    [1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach. Pearson, 2020. [2] F. Chollet, Deep Learning with Python. Manning Publications, 2018. [3] C. C. Aggarwal, Data Mining: The Textbook. Springer, 2015. [4] J. Dean and S. Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," Communications of the ACM, vol. 51, no. 1, pp. 107-113, 2008. [5] Apache Software Foundation, "Apache... - Source: dev.to / 3 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    If you're designing an event-based pipeline, you can use a data streaming tool like Kafka to process data as it's collected by the pipeline. For a setup that already has data stored, you can use tools like Apache Spark to batch process and clean it before moving ahead with the pipeline. - Source: dev.to / 4 months ago
View more

Octoparse mentions (3)

  • Thingiverse.com
    Octoparse.com might work, they have a very nice interactive tool + 14 day free trail. Source: over 3 years ago
  • How to Scrape and Export Products Data from Aliexpress
    These are no-code solutions for scraping websites. You don’t need any technical knowledge to scrape Aliexpress using these tools. Using advanced AI-powered click and scrape tools, you can get started scraping within seconds either locally or in the cloud. Choosing a good scraping tool can save you lots of money and time as well. Source: almost 4 years ago
  • Amazon web scraping
    I have always been able to extract data without any problems with Octoparse. It is also a very easy to use tool. Source: almost 4 years ago

What are some alternatives?

When comparing Apache Spark and Octoparse, you can also consider the following products

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

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.

Hadoop - Open-source software for reliable, scalable, distributed computing

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

Apache Storm - Apache Storm is a free and open source distributed realtime computation system.

ParseHub - ParseHub is a free web scraping tool. With our advanced web scraper, extracting data is as easy as clicking the data you need.

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