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.
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
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
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
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
A JVM based framework named "Spark", when https://spark.apache.org exists? - Source: Hacker News / 10 months ago
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
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 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
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
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
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