Based on our record, GraphQL seems to be a lot more popular than Google Cloud Dataflow. While we know about 247 links to GraphQL, we've tracked only 14 mentions of Google Cloud Dataflow. 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 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
Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 2 years ago
This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 2 years ago
I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 2 years ago
You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 2 years ago
It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / about 3 years ago
gRPC - Application and Data, Languages & Frameworks, Remote Procedure Call (RPC), and Service Discovery
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
React - A JavaScript library for building user interfaces
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
Next.js - A small framework for server-rendered universal JavaScript apps
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.