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Apache Spark VS Vercel

Compare Apache Spark VS Vercel 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.

Vercel logo Vercel

Vercel is the platform for frontend developers, providing the speed and reliability innovators need to create at the moment of inspiration.
  • Apache Spark Landing page
    Landing page //
    2021-12-31
  • Vercel Landing page
    Landing page //
    2023-08-05

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.

Vercel features and specs

  • Easy Deployment
    Vercel offers a straightforward and user-friendly process for deploying static sites and serverless functions. It integrates seamlessly with platforms like GitHub, GitLab, and Bitbucket, allowing developers to deploy directly from their repositories.
  • Fast Performance
    Vercel optimizes delivery through its global CDN, which ensures fast load times for users all around the world. It provides edge caching and real-time purging that contribute to high-performance web applications.
  • Serverless Functions
    Vercel supports serverless functions, enabling developers to build and deploy backend functionality without needing to manage server infrastructure. This can save time and resources, particularly for smaller projects.
  • Integration with Next.js
    Vercel is the creator of Next.js, a popular React framework, and offers seamless integration with it, providing advanced features like static site generation, server-side rendering, and API routes.
  • Scalability
    Vercel can handle increased traffic automatically, scaling web applications to accommodate a growing number of users without additional configuration.
  • Preview Deployments
    Every pull request can generate a unique preview deployment, allowing teams to preview changes in a live environment before merging. This enhances collaboration and speeds up the development process.

Possible disadvantages of Vercel

  • Cost
    While Vercel offers a free tier, the pricing can become expensive for larger projects or enterprises, particularly if they require more bandwidth, build minutes, or advanced features.
  • Serverless Limitations
    Serverless functions on Vercel have limits on execution time and computational power. This can be a constraint for compute-heavy tasks or long-running processes.
  • Vendor Lock-in
    Deploying heavily integrated projects with Vercel's proprietary features may make it difficult to migrate to another platform without significant rework.
  • Limited Backend Customization
    While Vercel supports serverless functions, it does not offer the same level of backend customization and control as traditional server hosting environments.
  • Learning Curve for Beginners
    Although easy deployment is a pro, beginners might find it complex to understand concepts like serverless architecture, environment variables, and project structure in the beginning.
  • Limited Language Support
    Vercel primarily supports JavaScript/TypeScript for serverless functions, potentially limiting the use for developers who prefer other programming languages for backend development.

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

Vercel videos

+ Add

Zeit Now - What is it?

More videos:

  • Review - Gorillaz - The Now Now ALBUM REVIEW
  • Review - Deploy Node.js Application to Zeit Now - FreeCodeCamp - Timestamp Microservice 04
  • Review - Now 100 Hits Forgotten 70's - The NOW Review
  • Review - AT&T TV Now 2020 Review - Is it GOOD now??
  • Review - Serverless Fullstack made easy with Next.js, Prisma 2, and Zeit Now #3: Set up Zeit Now

Category Popularity

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

Apache Spark

Vercel

Databases
100 100%
Databases
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Big Data
100 100%
Big Data
0% 0
Cloud Computing
0 0%
Cloud Computing
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 Spark and Vercel

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

Vercel Reviews

Top 10 Vercel v0 Open Source Alternatives | Medium
First things first, let’s talk about Vercel v0. You might be wondering, “What exactly is Vercel v0, and why should I care?” Well, my friend, Vercel v0 is a game-changing AI-powered development platform that’s been turning heads in the tech world. It’s designed to revolutionize the way we build and deploy web applications, making the process faster, smoother, and more...
Source: medium.com
5 Best Vercel Alternatives for Next.js & App Router
Vercel has become the go-to platform for hosting modern web applications built with frameworks like Next.js. However, as your application scales, Vercel's pricing model and lack of flexibility can become limiting.
Source: il.ly
Best Serverless Backend Tools of 2023: Pros & Cons, Features & Code Examples
Vercel is a platform for frontend developers for deploying code to an optimized production environment. Even though it doesn’t offer stateful features you’d expect from a BaaS like authentication or databases, it is trivial to copy/paste code from a third-party service like Auth0 for authentication and MongoAtlas for API development.
Source: www.rowy.io
Exploring alternatives to Vercel: A guide for web developers
In recent years, Vercel has emerged as a leading platform for deploying modern web applications, especially those built with frameworks like Next.js. Its seamless integration with Git, automatic deployments, and serverless functions have made it a go-to choice for many developers. However, Vercel can be quite expensive, especially for projects that scale, making it important...
Source: fleek.xyz
5 Free Heroku Alternatives with Free Plan for Developers
Vercel is last in my list and it is more like leys you host JavaScript based web apps and static websites. Since JS apps are in so much demand these days; you will find this platform easier to deploy your apps directly from GitHub/GitLab. It can even act as CI/CD pipeline for your projects. If you created a front end of an app then you can use it for deploying it. It lets...
Source: www.ilovefreesoftware.com

Social recommendations and mentions

Based on our record, Vercel should be more popular than Apache Spark. It has been mentiond 600 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.

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 / 26 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 / 28 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 / 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
View more

Vercel mentions (600)

  • Deploying a MERN full-stack web application on vercel.com (with Express and Vite as a monorepo)
    Create an account at Vercel with GitHub and authorize Vercel to see your private repo(s). - Source: dev.to / about 8 hours ago
  • Build a Personal Portfolio Website (2-Minute Tutorial)
    Upload your folder to Netlify, GitHub Pages, or Vercel — and boom, your portfolio is online! - Source: dev.to / 4 days ago
  • How to Build a simple REST API with Node, Express and MongoDB
    For deployment, you can host your server on platforms like Heroku and Vercel. Both platforms offer free tiers, making it easy to deploy your REST API. - Source: dev.to / 11 days ago
  • ArNext - Next.js framework that supports Arweave and Vercel simultaneously
    ArNext is a NextJS-based framework that lets you deploy the same codebase both on Vercel and Arweave. - Source: dev.to / 10 days ago
  • Why devs are quitting aws and what they’re choosing instead
    Platforms like Railway, Render, Fly.io, Vercel, Supabase, and Cloudflare are leading the charge with a shared philosophy:. - Source: dev.to / 10 days ago
View more

What are some alternatives?

When comparing Apache Spark and Vercel, 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.

Next.js - A small framework for server-rendered universal JavaScript apps

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

Netlify - Build, deploy and host your static site or app with a drag and drop interface and automatic delpoys from GitHub or Bitbucket

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

GitHub Pages - A free, static web host for open-source projects on GitHub

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