Enqueue It
Hangfire
Sidekiq
delayed_job
Resque
Celery
RabbitMQ
Strapi
Hadoop
Apache Spark
PostgreSQL
Apache Flink
Apache Cassandra
MongoDB
Apache Storm
Apache Kafka
Easy and scalable solution for managing and executing background tasks and microservices seamlessly in .NET applications. It allows you to schedule, queue, and process your jobs and microservices efficiently.
Designed to support distributed systems, enabling you to scale your background processes and microservices across multiple servers. With advanced features like performance monitoring, exception logging, and integration with various storage types, providing complete control and visibility over your workflow.
Provides a user-friendly web dashboard that allows you to monitor and manage your jobs and microservices from a centralized location. You can easily check the status of your tasks, troubleshoot issues, and optimize performance.
EnqueueIt is available for both .NET and Go.
The .NET packages support all EnqueueIt functionality, including the web dashboard and background jobs, which are exclusively available in the .NET package. The Go package was created as a lightweight alternative for running the EnqueueIt server, enabling the execution of microservices and seamless data synchronization between Redis and SQL databases. Additionally, the Go package supports the enqueueing and scheduling of microservices from Go, as well as the feature of reading microservice arguments.
Enqueue It HadoopEnqueue It's answer
dotnet and golang software engineers
Enqueue It's answer
Enqueue It's answer
It is completely opensource and free. the performance is unbeatable. it has no servers or apps limit when it come to be used in distribution systems.
Enqueue It's answer
dotnet golang redis postgresql mysql sqlserver oracle
Based on our record, Hadoop seems to be more popular. It has been mentiond 15 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
Hangfire - An easy way to perform background processing in .NET and .NET Core applications.
Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Sidekiq - Sidekiq is a simple, efficient framework for background job processing in Ruby
PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.
delayed_job - Database based asynchronous priority queue system -- Extracted from Shopify - collectiveidea/delayed_job
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
