Based on our record, Amazon EMR should be more popular than Raygun. It has been mentiond 10 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.
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: over 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: about 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
Raygun is a cloud-based platform that makes sure your web and mobile applications are free of errors, as well as your users are satisfied. It specializes in JavaScript error monitoring and offers a wide range of features to help you easily detect and fix issues. - Source: dev.to / 5 months ago
We can make the process a little easier by using our agile processes together with a continuous deployment strategy. For example, our friends at Raygun, discovered that “when a team gets locked into a sprint it can become much harder to recognize and fix bugs”. - Source: dev.to / 9 months ago
Regarding your last question, when I mention sub-processors who we don't have an SCC with I'm thinking about vendors like RayGun. It's a system we use to monitor alerts and warnings coming from our app when in the hands of our end-users. We have configured the tool so we get absolutely no personal information - no names, emails, id's or any of that sort. It's nothing more than technical data dumps from the inner... Source: over 1 year ago
Error logging and monitoring are crucial for any application, Appwrite being no exception. We wanted to make it extremely easy to collect and monitor your logs while staying true to our philosophy of being completely platform agnostic. With Appwrite 0.12, we've introduced support for some amazing open source logging providers like Sentry, Raygun and AppSignal! - Source: dev.to / over 2 years ago
We have RayGun for logging/reporting on the client-side of the apps. They are showing nothing interesting from those devices. They seem to fail silently. Source: almost 3 years ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Sentry.io - From error tracking to performance monitoring, developers can see what actually matters, solve quicker, and learn continuously about their applications - from the frontend to the backend.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Rollbar - Rollbar collects errors that happen in your application, notifies you, and analyzes them so you can debug and fix them. Ruby, Python, PHP, Node.js, JavaScript, and Flash libraries available.
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.