Based on our record, Amazon SQS should be more popular than Apache Storm. It has been mentiond 64 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 several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 1 year ago
Although this article lists a lot of targets for technical selection, there are definitely others that I haven't listed, which may be either outdated, less-used options such as Apache Storm or out of my radar from the beginning, like JAVA ecosystem. - Source: dev.to / over 1 year ago
Storm, a system for real-time and stream processing. - Source: dev.to / over 1 year ago
Google has scaled well and has helped others scale, Twitter has always been behind by years. I think the only thing they did well was Twitter Storm, now taken up by Apache Foundation. Source: over 1 year ago
Streaming: Sparks Streamings's latency is at least 500ms, since it operates on micro-batches of records, instead of processing one record at a time. Native streaming tools like Storm, Apex or Flink might be better for low-latency applications. - Source: dev.to / over 2 years ago
SQS - 1 million messaging queue requests. - Source: dev.to / 3 months ago
The last stage is productionizing the model. The goal of this phase is to create a system to process each image/video, gather the relevant features and inputs to the models, integrate the models into a hosting service, and relay the corresponding model predictions to downstream consumers like the MCF system. We used an existing Safety service, Content Classification Service, to implement the aforementioned system... Source: 5 months ago
For context; the web application is built with React and TypeScript which makes calls to an AppSync API that makes use of the Lambda and DynamoDB datasources. We use Step Functions to orchestrate the flow of events for complex processing like purchasing and renewing policies, and we use S3 and SQS to process document workloads. - Source: dev.to / 6 months ago
Amazon SQS is a fully managed message queue service that provides a reliable and scalable solution for asynchronous messaging between distributed components and microservices. - Source: dev.to / 9 months ago
The key service that publishes messages to its subscribers is Simple Notification Service (SNS). We can add multiple different subscribers to a topic, for example, email addresses, phone numbers, or SQS queues. - Source: dev.to / 11 months ago
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
RabbitMQ - RabbitMQ is an open source message broker software.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
Amazon SNS - Fully managed pub/sub messaging for microservices, distributed systems, and serverless applications