Apache Pig is recommended for data engineers and analysts who are working in Apache Hadoop environments and need to perform ETL (Extract, Transform, Load) operations on large datasets. It is also suitable for teams looking to leverage existing Hadoop infrastructures without delving into complex Java MapReduce programming or when migrating legacy processing scripts based on Pig Latin.
Based on our record, GraphQL seems to be a lot more popular than Apache Pig. While we know about 247 links to GraphQL, we've tracked only 2 mentions of Apache Pig. 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.
Pig, a platform/programming language for authoring parallelizable jobs. - Source: dev.to / over 2 years ago
In the early days of the Big Data era when K8s hasn't even been born yet, the common open source go-to solution was the Hadoop stack. We have written several old-fashioned Map-Reduce jobs, scripts using Pig until we came across Spark. Since then Spark has became one of the most popular data processing engines. It is very easy to start using Lighter on YARN deployments. Just run a docker with proper configuration... - Source: dev.to / over 3 years ago
Recently, I started exploring GraphQL while working on my MERN stack project. I learnt this through some youtube videos and some Other sources. Https://graphql.org/. - Source: dev.to / 14 days ago
Sonja Keerl, CTO of MACH Alliance, states, "Composable architectures enable enterprises to innovate faster by assembling best-in-class solutions." Developers must embrace technologies like GraphQL, gRPC, and OpenAPI to remain competitive. - Source: dev.to / 26 days ago
📌 Learn more about GraphQL: https://graphql.org/. - Source: dev.to / 3 months ago
Nest.js has been most widely adopted in developing back-end applications such as RESTful APIs, GraphQL services, and microservices. With its modular design, this framework is well and truly set for large project management; it allows for smooth and efficient performance through built-in features such as dependency injection and strong middleware support. - Source: dev.to / 4 months ago
Overview: Managing data efficiently is crucial for delivering smooth user experiences in today's fast-paced digital world. One technology that has revolutionized data handling in web development is GraphQL. This query language for APIs has transformed the way developers interact with data sources, offering flexibility, efficiency, and speed. - Source: dev.to / 4 months ago
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
gRPC - Application and Data, Languages & Frameworks, Remote Procedure Call (RPC), and Service Discovery
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
React - A JavaScript library for building user interfaces
Presto DB - Distributed SQL Query Engine for Big Data (by Facebook)
Next.js - A small framework for server-rendered universal JavaScript apps