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Windsurf Editor VS Apache Spark

Compare Windsurf Editor VS Apache Spark and see what are their differences

Flagsmith
Flagsmith lets you manage feature flags and remote config across web, mobile and server side applications. Deliver true Continuous Integration. Get builds out faster. Control who has access to new features. We're Open Source. featured
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Windsurf Editor logo Windsurf Editor

Tomorrow's editor, today. Windsurf Editor is the first AI agent-powered IDE that keeps developers in the flow. Available today on Mac, Windows, and Linux.

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.
  • Windsurf Editor Landing page
    Landing page //
    2025-02-16
  • Apache Spark Landing page
    Landing page //
    2021-12-31

Windsurf Editor features and specs

  • User-Friendly Interface
    Windsurf Editor features an intuitive and easy-to-navigate interface, making it accessible for users of all experience levels.
  • Real-Time Editing
    Allows for real-time editing, enabling users to see changes immediately and facilitate a faster workflow.
  • Cloud-Based
    Being a cloud-based editor, it ensures that users can access their projects from anywhere and collaborate with others easily.
  • Integration Capabilities
    Offers seamless integration with various third-party applications and services, enhancing functionality and flexibility.

Possible disadvantages of Windsurf Editor

  • Internet Dependency
    Requires a stable internet connection to function, which may be a limitation for users with poor connectivity.
  • Limited Offline Features
    Offers limited offline capabilities, which can hinder productivity for those needing to work without internet access.
  • Subscription Cost
    May involve subscription fees that can be a disadvantage for individuals or businesses on a tight budget.
  • Learning Curve for Advanced Features
    While the basic features are easy to use, mastering advanced features might require more time and effort.

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 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.

Windsurf Editor videos

+ Add

Is Windsurf Editor Better Than Cursor AI?

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

Category Popularity

0-100% (relative to Windsurf Editor and Apache Spark)

Windsurf Editor

Apache Spark

AI
100 100%
AI
0% 0
Databases
0 0%
Databases
100% 100
Developer Tools
100 100%
Developer Tools
0% 0
Big Data
0 0%
Big Data
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 Windsurf Editor and Apache Spark

Windsurf Editor Reviews

Cursor vs Windsurf vs GitHub Copilot
Now, don't get me wrong, both Windsurf and Copilot are solid tools. Copilot is great for quick suggestions across different IDEs, and Windsurf impresses with its polished UI and intuitive workflow. Windsurf's Cascade feature even offers sophisticated real-time collaboration, comprehensive project understanding, and seamless context awareness that rivals Cursor's capabilities.
Source: www.builder.io

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

Social recommendations and mentions

Based on our record, Apache Spark should be more popular than Windsurf Editor. It has been mentiond 70 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.

Windsurf Editor mentions (12)

  • My Experience at Commit Conf 2025
    AI is replacing traditional platforms like Stack Overflow, Reddit, and Google Search for developers — tools like GitHub Copilot, Cursor.ai, and Windsurf are seen as faster, more tailored, and more efficient. - Source: dev.to / about 7 hours ago
  • Create a feature flag in your IDE in 5 minutes with LaunchDarkly’s MCP server
    The Cursor IDE installed on your local machine. Although this tutorial is Cursor-focused, our MCP server also works with any AI client that supports MCP, such as Windsurf or even Raycast. - Source: dev.to / 1 day ago
  • Supercharge Your Observability: How OTEL MCP Server Unlocks AI-Powered Insights
    The true power of OTEL MCP Server emerges when integrated with AI-powered tools like Windsurf, creating a seamless bridge between code and telemetry data. - Source: dev.to / 8 days ago
  • How to Use Claude 4 Opus & Sonnet with Cursor & Windsurf
    Windsurf AI Editor is a modern, lightweight, and AI-first code editor designed for developers who want to deeply integrate large language models like Claude 4 Opus and Sonnet into their development workflow. Unlike traditional editors, Windsurf isn’t just a place to write code — it’s where code collaborates with you. - Source: dev.to / 13 days ago
  • Engineering with AI: Adapting Core Practices for LLM-Driven Development
    The core idea behind Rulebook-AI is not to build another AI coding assistant from scratch, nor is it to create a new IDE. Instead, it aims to be an orchestration and customization layer that sits on top of existing AI coding assistants (like Cursor, CLINE, RooCode, and Windsurf). Its primary goal, as outlined in its PRD, is to "provide a comprehensive and optimal Custom User Prompt (Rules) framework" and leverage... - Source: dev.to / 28 days ago
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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 — can read and/or write Iceberg data directly. - Source: dev.to / about 1 month 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 1 month 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

What are some alternatives?

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

Cursor - The AI-first Code Editor. Build software faster in an editor designed for pair-programming with AI.

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

GitHub Copilot - Your AI pair programmer. With GitHub Copilot, get suggestions for whole lines or entire functions right inside your editor.

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

Fynix.ai - Fynix accelerates your software development with real-time AI assistance, automated code reviews, and tools for documentation, diagram creation, and system reliability.

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

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