Software Alternatives & Reviews

Apache Spark VS GraphQL

Compare Apache Spark VS GraphQL and see what are their differences

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.

GraphQL logo GraphQL

GraphQL is a data query language and runtime to request and deliver data to mobile and web apps.
  • Apache Spark Landing page
    Landing page //
    2021-12-31
  • GraphQL Landing page
    Landing page //
    2023-08-01

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

GraphQL videos

REST vs. GraphQL: Critical Look

More videos:

  • Review - REST vs GraphQL - What's the best kind of API?
  • Review - What Is GraphQL?

Category Popularity

0-100% (relative to Apache Spark and GraphQL)
Databases
100 100%
0% 0
Developer Tools
0 0%
100% 100
Big Data
100 100%
0% 0
Javascript UI Libraries
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 Apache Spark and GraphQL

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...

GraphQL Reviews

We have no reviews of GraphQL yet.
Be the first one to post

Social recommendations and mentions

Based on our record, GraphQL should be more popular than Apache Spark. It has been mentiond 223 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 (56)

  • Groovy 🎷 Cheat Sheet - 01 Say "Hello" from Groovy
    Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉. - Source: dev.to / about 2 months ago
  • 🦿🛴Smarcity garbage reporting automation w/ ollama
    Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system. - Source: dev.to / 3 months ago
  • Go concurrency simplified. Part 4: Post office as a data pipeline
    Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 4 months ago
  • Five Apache projects you probably didn't know about
    Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 4 months ago
  • Spark – A micro framework for creating web applications in Kotlin and Java
    A JVM based framework named "Spark", when https://spark.apache.org exists? - Source: Hacker News / 10 months ago
View more

GraphQL mentions (223)

  • Building Scalable GraphQL Microservices With Node.js and Docker: A Comprehensive Guide
    GraphQL is a query language and runtime for APIs. It provides a flexible and efficient way for clients to request and retrieve specific data from a server using a single API endpoint. - Source: dev.to / 15 days ago
  • Type-Safe Fetch with Next.js, Strapi, and OpenAPI
    When you use technologies like GraphQL, it is trivial to derive TypeScript types. A GraphQL API is created by implementing a schema. Generating the TypeScript type definitions from this schema is simple, and you do not have to do any more work than just making the GraphQL API. This is one reason why I like GraphQL so much. - Source: dev.to / 23 days ago
  • REST vs. GraphQL: A Detailed Comparison of API Architectures for Developers
    REST and GraphQL have advantages, drawbacks, and use cases for different environments. REST is for simple logic and a more structured architecture, while GraphQL is for a more tailored response and flexible request. - Source: dev.to / 29 days ago
  • Gatsby tutorial: Build a static site with a headless CMS
    A Gatsby site uses Gatsby, which leverages React and GraphQL to create fast and optimized web experiences. Gatsby is often used for building static websites, progressive web apps (PWAs), and even full-blown dynamic web applications. - Source: dev.to / about 1 month ago
  • Rust GraphQL APIs for NodeJS Developers: Introduction
    In my usual NodeJS tech stack, which includes GraphQL, NestJS, SQL (predominantly PostgreSQL with MikroORM), I encountered these limitations. To overcome them, I've developed a new stack utilizing Rust, which still offers some ease of development:. - Source: dev.to / 6 months ago
View more

What are some alternatives?

When comparing Apache Spark and GraphQL, 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.

gRPC - Application and Data, Languages & Frameworks, Remote Procedure Call (RPC), and Service Discovery

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

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

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

React - A JavaScript library for building user interfaces