No deepstream.io videos yet. You could help us improve this page by suggesting one.
Amazon EMR might be a bit more popular than deepstream.io. We know about 10 links to it since March 2021 and only 9 links to deepstream.io. 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.
What your trying to do is very difficult (particularly since your data views are relying upon joins and group queries.) You may need layered solutions. I've been looking at https://deepstream.io for keeping clients in sync. You will still have to watch the db, though the client and back end sync is handled! - Source: Hacker News / 15 days ago
Https://deepstream.io/ - a popular open source realtime server and https://golden-layout.com/ - the leading layout manager for Web Apps - among many other things. You can find more examples of my work at https://wolframhempel.github.io/me/ My specialties are complex, graphically demanding Web Apps and Cloud server architectures. Over the years I've gotten incredibly good at helping my clients deliver some of the... - Source: Hacker News / 4 months ago
Wolfram previously built https://arcentry.com/, https://deepstream.io/ and https://golden-layout.com/, Adam is Director of Engineering for a trading tech company and. - Source: Hacker News / 10 months ago
OS projects: https://deepstream.io/, https://vramework.io/. - Source: Hacker News / over 1 year ago
Deepstream is an open-source library for real-time web application development. The library, which is built with Node.js and Engine.io, helps developers build frontend web applications that perform real-time updates while requiring minimal backend code. - Source: dev.to / over 1 year ago
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 1 year 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 2 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: almost 2 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 2 years ago
Check out https://aws.amazon.com/emr/. Source: about 2 years ago
Socket.io - Realtime application framework (Node.JS server)
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
PubNub - PubNub is a real-time messaging system for web and mobile apps that can handle API for all platforms and push messages to any device anywhere in the world in a fraction of a second without having to worry about proxies, firewalls or mobile drop-offs.
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost