Software Alternatives, Accelerators & Startups

Bright Data VS Apache Spark

Compare Bright Data VS Apache Spark and see what are their differences

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Bright Data logo Bright Data

World's largest proxy service with a residential proxy network of 72M IPs worldwide and proxy management interface for zero coding.

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.
  • Bright Data Landing page
    Landing page //
    2021-05-12
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Bright Data features and specs

  • Extensive Proxy Network
    Bright Data offers a vast and diverse network of over 72 million IPs, ensuring high availability and reliability for users.
  • Wide Range of Services
    Provides various proxy solutions including data center, residential, mobile, and ISP proxies, catering to different user needs.
  • Geographical Targeting
    Allows users to target proxies based on specific countries, cities, and even ASN, which is beneficial for localized data scraping.
  • Advanced Tools and APIs
    Offers sophisticated tools and APIs for automation, data extraction, and optimized proxy management.
  • Customer Support
    Provides round-the-clock customer support and numerous resources such as detailed documentation and integration guides.

Possible disadvantages of Bright Data

  • Cost
    Bright Data's services are priced at a premium, which might be expensive for small businesses or individual users.
  • Complexity
    The extensive range of options and settings can be overwhelming and may require a steep learning curve for new users.
  • Ethical Concerns
    The use of residential and mobile proxies can raise ethical questions regarding user consent and data privacy.
  • Account Approval
    New accounts are subject to approval which can delay immediate access to the service.
  • Occasional IP Blocks
    Despite the large IP pool, users may still experience occasional blocks and captchas when accessing certain websites.

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.

Analysis of Bright Data

Overall verdict

  • Bright Data is generally considered a good choice for businesses and professionals who require reliable and scalable proxy services. It excels in offering a comprehensive set of features and a vast IP pool, although it might be considered expensive for individual or small-scale users.

Why this product is good

  • Bright Data, formerly known as Luminati Networks, is a well-regarded proxy service provider known for its vast network of IP addresses and wide range of proxy types. It offers residential, data center, and mobile proxies with a focus on reliability and scalability. The service is often praised for its high uptime, excellent customer support, and robust infrastructure, making it a popular choice for businesses needing large-scale data collection and web scraping solutions.

Recommended for

  • Large enterprises needing mass data collection
  • Businesses engaged in web scraping and analysis
  • Companies requiring high uptime and reliability
  • Professionals interested in diverse proxy options, including residential and mobile

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.

Bright Data videos

Rotating Residential Network | Proxy Network Types | Bright Data (Formerly Luminati Networks)

Apache Spark videos

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

Category Popularity

0-100% (relative to Bright Data and Apache Spark)
Proxy
100 100%
0% 0
Databases
0 0%
100% 100
Residential Proxies
100 100%
0% 0
Big Data
0 0%
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 Bright Data and Apache Spark

Bright Data Reviews

  1. Sam Mitchell
    ยท Owner at KittenProperties ยท
    Mixed feelings

    We used their DC proxies and Residential proxies. Resi proxies were having quite low success rate. We had to use resi solution from other proxy providers. Unblocker didn't work well either also it was way too expensive.

    ๐Ÿ Competitors: Decodo, NetNut.io
    ๐Ÿ‘ Pros:    Cheap dc proxies
    ๐Ÿ‘Ž Cons:    Quite expensive|Residential proxies are worse than competitiors

Proxy Service Awards 2024
And if thereโ€™s one thing that defines Bright Data in an industry where all gaps are closing, itโ€™s the platform. Weโ€™ve criticized it for complexity and opaqueness; but after all these years, we have to admit that Bright Dataโ€™s tooling remains a north star for many providers aspiring to serve the most demanding clients.
Source: proxyway.com
Top 10 Alternatives to Bright Data (formerly Luminati Proxy Networks)
Oxylabs remains the number aggressive competitor of Bright Data โ€“ they have even had a case to settle in the court in the past. If you wouldnโ€™t want to use Bright Data proxies, then you might as well avoid Oxylabsas it is everything you hate in Bright Data and even worse. Aside from the pricing aspect, Oxylabs have been found to engage in some unethical practices and scam...
911.re Alternatives: 10 Best Proxies Smilar to 911 Proxy in 2023
The most exciting thing about Bright Data is that it comes with new daily feature releases so that you always have access to the latest features as soon as they are released. You also have access to 24/7 global support and dedicated account managers who will help you get started with Bright Data immediately!
17 BEST Residential Proxies to Buy in 2022 (Cheap & Premium)
Formerly known as Luminati Networks, Bright Data is the most popular premium residential proxy provider in the industry.
Source: earthweb.com
10 Best Free Online Proxy Server List of 2022 [VERIFIED]
Verdict: Bright Data Proxy Manager will help you with various use cases such as web data extraction, e-commerce, collecting stock market data, brand protection, etc. Bright Data has capabilities of data collection from eCommerce, Social Media, etc. It provides 24ร—7 global support and dedicated account managers.

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...
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 โ€“ 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...
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...

Social recommendations and mentions

Based on our record, Apache Spark should be more popular than Bright Data. It has been mentiond 80 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.

Bright Data mentions (45)

  • Precursor
    Happy to offer a counter of some great products for anti-bot defeat: https://brightdata.com/ https://www.zenrows.com/ https://www.capsolver.com/ https://scrapfly.io/ hundreds of millions of residential ips, human browser fingerprints, custom browser binaries, auto solve of turnstyle, recaptcha v3, kasada, datadome, AWS WAF, etc if they come up. - Source: Hacker News / about 1 month ago
  • Best Web Scraping Tools in 2026: A Hands-On Comparison of the Top 10
    The best web scraping tools 2026 leaderboard hasn't changed; the gap has narrowed. Bright Data remains the safest bet for any team that wants to spend time on the data, not on the scraping. The 660-scraper library, 400M-IP network, pay-per-success pricing and unlimited concurrency are still uncontested at the high end. - Source: dev.to / 3 months ago
  • The Economics of Web Scraping: How Consultancies Price Data Extraction and Manage Scope Creep
    Infrastructure Pass-Through (OpEx) Data extraction at scale is infrastructure-heavy. Bypassing modern Web Application Firewalls (WAFs) requires high-quality residential proxies, CAPTCHA solvers, and substantial browser-automation compute resources. Services like Bright Data charge significantly by the gigabyte for premium residential IPs. These variable infrastructure costs must be passed directly to the client,... - Source: dev.to / 4 months ago
  • LinkedIn Scraping Is Dead: 5 Legal, ToS-Safe Alternatives That Actually Work in 2026
    Bright Data has successfully defended web scraping in U.S. Courts and offers LinkedIn datasets pre-collected and ready to download. LinkedIn profile data on their dataset marketplace runs around $250 per 100,000 records. The freshness caveat is real: bulk datasets are snapshots, not real-time. If you need current job titles on a rolling basis, you're better with an enrichment API than a one-time dataset pull.... - Source: dev.to / 4 months ago
  • Building a Live AI Market Research Terminal: How Bright Data and Convex Replace Polling With Real-Time Everything
    Bright Data built an open-source demo that solves this. It's called the Signal Terminal, a financial research tool built around that problem. - Source: dev.to / 5 months ago
View more

Apache Spark mentions (80)

  • MLOps Lifecycle: Stages, Workflow, and Best Practices
    Feature transformations should be deterministic: The same input should produce the same output when the same feature definition and configuration are applied. This is what allows training, backtesting, and live inference to remain aligned. Tools such as Pandas, Spark, or feature platforms such as Feast can be used to implement that logic. - Source: dev.to / 2 months ago
  • 7 Free Tools for Data Pipeline Reconciliation and Cross-Source Validation
    Apache Spark provides distributed in-memory data processing and is the appropriate tool when the data set to be reconciled does not fit in a single machine's memory, or when parallelizing the comparison across a cluster would reduce runtime from hours to minutes. - Source: dev.to / 3 months ago
  • Why Apache IoTDB Is Written in Java: A Decade of Engineering Trade-offs
    When IoTDB was initiated in 2011, almost all influential distributed systems and databases were built in Java or on the JVMโ€”such as Hadoop, HBase, Spark (Scala on JVM), Cassandra, Kafka, and Flink. To integrate deeply with the big data ecosystem, choosing Java was a natural decision. - Source: dev.to / 5 months ago
  • I Scraped 47M+ Hacker News Items Into Parquet Files โ€“ Here's What I Discovered About HN's Hidden Data Patterns
    For handling even larger datasets or building production applications, Apache Spark provides excellent Parquet support with distributed processing capabilities. - Source: dev.to / 5 months ago
  • Show HN: Spark โ€“ Zero-config IoT deployment tool written in Rust
    You may want to consider renaming this project. The name "Spark" already refers to: A popular data analytics framework of the Apache Foundation: https://spark.apache.org/ A subset of the Ada programming language used for formal verification: https://learn.adacore.com/courses/intro-to-spark/chapters/01_Overview.html An Nvidia AI development system: https://www.nvidia.com/en-us/products/workstations/dgx-spark/. - Source: Hacker News / 7 months ago
View more

What are some alternatives?

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

Oxylabs - A web intelligence collection platform and premium proxy provider, enabling companies of all sizes to utilize the power of big data.

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

Decodo - Decodo is perhaps the most user-friendly way to access local data anywhere. It has global coverage with 195 locations, offers more than 55M residential proxies worldwide and a great deal of scraping solutions.

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

NetNut.io - Residential proxy network with 52M+ IPs worldwide. SERP API, Website Unblocker, Professional Datasets.

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