Based on our record, Amazon SQS should be more popular than Hadoop. It has been mentiond 65 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.
Did you check out tools like https://hadoop.apache.org/ ? Source: about 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
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 1 year ago
A copy of Hadoop installed on each of these machines. You can download Hadoop from the Apache website, or you can use a distribution like Cloudera or Hortonworks. - Source: dev.to / over 1 year ago
The Apache™ Hadoop™ project develops open-source software for reliable, scalable, distributed computing. - Source: dev.to / over 1 year ago
Event Routers: Services like Amazon SQS (A managed message queuing), Amazon SNS (A pub/sub messaging), AWS Step Functions (An orchestrate serverless workflows) and Amazon EventBridge (A serverless event bus) act as event routers, establishing the paths and flow for messages within the architecture. They enable seamless handling and distribution of events, ensuring that each message reaches its intended destination... - Source: dev.to / 9 days 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
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 Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.
Apache Kafka - Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Amazon SNS - Fully managed pub/sub messaging for microservices, distributed systems, and serverless applications