Amazon EMR is recommended for data engineers, data scientists, and IT professionals who need to manage and process large datasets in a scalable, efficient, and cost-effective manner. It is especially suitable for businesses that are already using AWS services and want to leverage a tightly integrated ecosystem. Additionally, it is a good choice for organizations that require rapid and flexible data analysis capabilities provided by frameworks such as Hadoop, Spark, HBase, and Presto.
Based on our record, Firebase seems to be a lot more popular than Amazon EMR. While we know about 272 links to Firebase, we've tracked only 10 mentions of Amazon EMR. 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.
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 2 years ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 3 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 3 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 3 years ago
Check out https://aws.amazon.com/emr/. Source: about 3 years ago
There is little mention of realtime on the Firebase landing page https://firebase.google.com We likely agree that firebase is superb. But your criticism of using ‘alternative’ is unjust both in terms of the breadth of firebase, and why a competitor might target someone about to choose Firebase. - Source: Hacker News / 4 days ago
Presumably Google AI Studio[1] and Google Firebase Studio[2] are made by different teams with very similar pitches, and Google is perfectly happy to have both of them exist, until it isn't: - AI Studio: "the fastest place to start building with the Gemini API" - Firebase Studio: "Prototype, build, deploy, and run full-stack, AI apps quickly" [1] https://aistudio.google.com/apps [2] https://firebase.google.com/. - Source: Hacker News / 8 days ago
Firebase provides a suite of tools and services designed to streamline the development process, abstracting away complex infrastructure management. Cloud Functions, a key component of the Firebase ecosystem, empowers developers to write and deploy backend code without the burden of provisioning or managing servers. This allows them to focus solely on writing the application logic, freeing up time and resources for... - Source: dev.to / 29 days ago
Supabase is an open-source Firebase alternative that provides a full backend out of the box — including a PostgreSQL database, authentication, file storage, and auto-generated APIs. It’s developer-friendly, easy to set up, and integrates smoothly with frontend frameworks like Vue. - Source: dev.to / about 1 month ago
In this tutorial, you will learn how to build a job application and interviewing platform using Next.js, Stream, and Firebase. This app will allow recruiters to post job openings, review applications, and schedule interviews. Job seekers can also apply for jobs and communicate with recruiters. - Source: dev.to / about 1 month ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Supabase - An open source Firebase alternative
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Android Studio - Android development environment based on IntelliJ IDEA
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
Socket.io - Realtime application framework (Node.JS server)