Based on our record, Amazon EMR should be more popular than Drools. 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.
See https://cacm.acm.org/magazines/2023/6/273222-the-silent-revolution-of-sat/fulltext and also modern production rules engines like https://drools.org/ Oddly, back when “expert system shells” were cool people thought 10,000 rules were difficult to handle, now 1,000,000 might not be a problem at all. Back then the RETE algorithm was still under development and people were using linear search and not hash tables... - Source: Hacker News / 4 months ago
Drools – an open-source business rule management system that allows developers to create and manage complex decision logic. Source: 12 months ago
- Drools - Available in JVM environments (Java, Scala and similar) - uses FEEL for expression language. Source: about 1 year ago
GoRules is a modern, open-source rules engine designed for high performance and scalability. Our mission is to democratise rules engines and drive early adoption. Rules engines are very useful as they allow business users to easily understand and modify core business logic with little help from developers. You can think of us as a modern, less memory-hungry version of Drools that will be available in many... Source: about 1 year ago
Is this something like Drools? It's quite uncommon but it is used in situations where certain sets of business rules change a lot and you want business analysts to be able to quickly change them in a simple graphical UI. Source: over 2 years 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
Camunda - The Universal Process Orchestrator
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
DecisionRules.io - Business rule engine that lets you create and deploy business rules, while all your rules run in a secure and scalable cloud. Unlike other rule engines, you can create your first rule in 5 minutes and make 100k decisions in a minute via API.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
jBPM - jBPM is a flexible Business Process Management (BPM) Suite.
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost