AWS Data Wrangler
Dask
Apache Spark
Kafka
Serverspec
Celery
Apache Airflow
RSpec
Enqueue It
Hangfire
Sidekiq
delayed_job
Resque
Celery
RabbitMQ
Strapi
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.
AWS Data Wrangler 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, AWS Data Wrangler seems to be more popular. It has been mentiond 4 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.
I had no problem with awswrangler (https://github.com/aws/aws-sdk-pandas) and it supports reading and writing partitions which was really helpful and a few other optimizations that made it a great tool. Source: 5 months ago
Awslabs has developed their own package for this and given it's for their product, seem likely to maintain it. https://github.com/awslabs/aws-data-wrangler. Source: over 2 years ago
AWS data wrangler works well. it's a wrapper on pandas: https://github.com/awslabs/aws-data-wrangler. Source: over 2 years ago
Yep, agreed. Go is a great language for AWS Lambda type workflows. Python isn't as great (Python Lambda Layers built on Macs don't always work). AWS Data Wrangler (https://github.com/awslabs/aws-data-wrangler) provides pre-built layers, which is a work around, but something that's as portable as Go would be the best solution. - Source: Hacker News / about 3 years ago
Dask - Dask natively scales Python Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love
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
Kafka - Apache Kafka is publish-subscribe messaging rethought as a distributed commit log.
delayed_job - Database based asynchronous priority queue system -- Extracted from Shopify - collectiveidea/delayed_job
