Software Alternatives, Accelerators & Startups

ASP.NET VS Apache Spark

Compare ASP.NET VS Apache Spark and see what are their differences

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ASP.NET logo ASP.NET

ASP.NET is a free web framework for building great Web sites and Web applications using HTML, CSS and JavaScript.

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.
  • ASP.NET Landing page
    Landing page //
    2023-04-29
  • Apache Spark Landing page
    Landing page //
    2021-12-31

ASP.NET features and specs

  • Performance
    ASP.NET is known for its high performance and scalability. It compiles server-side code to DLL files, which is executed on the server side, thereby speeding up the application's response time.
  • Security
    ASP.NET provides built-in security features like form authentication and Windows authentication, as well as protection against common threats such as SQL injection, cross-site scripting, and request forgery.
  • Rich Toolbox
    Visual Studio, the Integrated Development Environment (IDE) for ASP.NET, offers a rich toolbox with a plethora of controls, automatic deployment features, and other tools that significantly speed up development.
  • Cross-Platform Support
    ASP.NET Core is a cross-platform framework, which means you can run your web applications on Windows, Linux, and macOS.
  • Community and Support
    ASP.NET has a strong community and extensive documentation, making it easier to find solutions to problems and ensuring continuous improvement and support.

Possible disadvantages of ASP.NET

  • Learning Curve
    The framework can be complex for beginners, especially those without experience in C# or the .NET ecosystem.
  • Cost
    While ASP.NET Core is free and open-source, some advanced features and tools require a Visual Studio subscription, which can be expensive.
  • Hosting
    Although ASP.NET Core has improved in terms of cross-platform hosting, traditional ASP.NET applications are primarily optimized for Windows servers, limiting hosting options.
  • Resource Intensive
    ASP.NET applications can be more resource-intensive than applications built with some other frameworks, which can lead to higher infrastructure costs.
  • Complexity
    The framework offers a lot of features and functionalities, which can sometimes make it overly complex and harder to manage for smaller projects.

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.

ASP.NET videos

Build Rating and Review System in ASP.NET MVC and Entity Framework

More videos:

  • Review - ASP.NET MVC - Review 0
  • Review - IMDeanyP Movie Review Site - ASP.NET / C# / SQL Server / MVC / Entity Framework

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 ASP.NET and Apache Spark)
Developer Tools
100 100%
0% 0
Databases
0 0%
100% 100
Web Frameworks
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 ASP.NET and Apache Spark

ASP.NET Reviews

The 20 Best Laravel Alternatives for Web Development
ASP.NET’s got that Microsoft muscle, a powerhouse of a framework for building dynamic web services and more. It lets you roll out robust websites with the smoothness that comes with deep pockets. Perfect for .NET software development teams.
Top 10 Phoenix Framework Alternatives
Moving over to the .NET platform, Asp.Net is an open-source web framework developed by Microsoft that allows developers to build dynamic web pages, apps, and services using HTML, JavaScript, and CSS.
10 Ruby on Rails Alternatives For Web Development in 2022
Last but not least, a back-end web framework created by Microsoft for the development of dynamic web pages - ASP.NET. Built on top of C# it is one the fastest frameworks available on the market. ASP.NET is capable of handling 7.01 million requests per second while Django handles only 79,266 requests. The framework is mainly used for building web applications, APIs,...

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 – 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 ASP.NET. 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.

ASP.NET mentions (22)

  • 30,656 Pages of Books About the .NET Ecosystem: C#, Blazor, ASP.NET, & T-SQL
    Most of the books teach C# and .NET, ASP.NET, Blazor, or T-SQL. I also found some .NET-specific coverage of wider topics: architecture and design, concurrency, automated tests, functional programming, and dependency injection. - Source: dev.to / about 2 months ago
  • Diversify Your Tech Stack: Uncovering Powerful Node js Alternatives
    Built by Microsoft, .NET is a high-performance application platform that uses C# for programming. .NET is cross-platform and comes with plenty of libraries and APIs covering collections, networking, and machine learning to build different types of applications. ASP.NET Core widens the .NET developer platform with libraries and tools geared towards web applications. - Source: dev.to / 9 months ago
  • C# Fundamentals
    Web Applications: ASP.NET, a powerful framework for building web applications, is primarily based on C#. Developers can create dynamic websites, web APIs, and services with ASP.NET. - Source: dev.to / 11 months ago
  • What’s New in Bold Reports 6.1 April 2024 Release
    The Bold Reporting Tools ASP.NET MVC and ASP.NET Web Forms will no longer be deployed in the embedded build. However, bug fixes are diligently transferred to our public repositories until Microsoft officially announces the end of support for these platforms. For new web application development or to stay up-to-date, Blazor or ASP.NET Core are recommended. - Source: dev.to / about 1 year ago
  • Is ASP.NET Core the next step in my career being an ASP.NET MVC developer? Or are there other technologies I should look at?
    Sorry for the possibly dumb questions. But then does .NET 5 have a "Model View Controller" workflow? I'm seeing ASP.NET still exists. But it's just "ASP.NET", no "MVC" or "Core" attached to the end. And they seem to recommend Blazor instead of C# which is something I only know the name of. Source: about 2 years 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 / 17 days 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 / 19 days 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 / about 2 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 / 2 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 / 3 months ago
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What are some alternatives?

When comparing ASP.NET and Apache Spark, you can also consider the following products

Ruby on Rails - Ruby on Rails is an open source full-stack web application framework for the Ruby programming...

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

Django - The Web framework for perfectionists with deadlines

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

Laravel - A PHP Framework For Web Artisans

Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.