Apache Spark
Apache Flink
Apache Airflow
Hadoop
Apache Kafka
Apache Storm
Google Cloud Dataflow
Apache Hive
Enqueue It
Hangfire
Sidekiq
delayed_job
Resque
RabbitMQ
Celery
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.
Apache Spark Enqueue ItEnqueue 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, Apache Spark seems to be more popular. It has been mentiond 56 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.
Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉. - Source: dev.to / about 2 months ago
Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system. - Source: dev.to / 3 months ago
Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 4 months ago
Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
A JVM based framework named "Spark", when https://spark.apache.org exists? - Source: Hacker News / 11 months ago
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Hangfire - An easy way to perform background processing in .NET and .NET Core applications.
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Sidekiq - Sidekiq is a simple, efficient framework for background job processing in Ruby
Hadoop - Open-source software for reliable, scalable, distributed computing
delayed_job - Database based asynchronous priority queue system -- Extracted from Shopify - collectiveidea/delayed_job
