Based on our record, Todoist seems to be a lot more popular than Amazon EMR. While we know about 131 links to Todoist, we've tracked only 10 mentions of Amazon EMR. 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'm curious how this is better than (or even significantly different to) Todoist [1], a well-established cross platform application which also supports natural language task creation [2] and a keyboard-driven workflow [3]. [1]: https://todoist.com/. - Source: Hacker News / 3 months ago
Todoist is renowned for its simplicity and powerful task management features, making it one of the best shared to-do list apps for couples in 2024. Whether it's managing household tasks or planning a big event, Todoist helps couples stay organized and focused. - Source: dev.to / 4 months ago
Todoist.com — Collaborative and individual task management. The free plan has: 5 active projects, five users in the project, file uploading up to 5MB, three filters, and one week of activity history. - Source: dev.to / 5 months ago
The official Todoist website can be found at https://todoist.com, and information about OpenAI is available at https://openai.com. The names Todoist and OpenAI as well as related names, marks, emblems, and images are registered trademarks of their respective owners. Source: 8 months ago
Tired of juggling endless to-do lists and struggling to stay organized? Todoist streamlines your task management with its user-friendly interface, allowing you to effortlessly create, categorize, and prioritize your daily tasks. There are many to-do list apps out there, but Todoist is one of the best. Beyond personal efficiency, Todoist is also a great collaborative tool for teams, with shared tasks, real-time... - Source: dev.to / 10 months 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: over 1 year ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: about 2 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 2 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
Check out https://aws.amazon.com/emr/. Source: about 2 years ago
Trello - Infinitely flexible. Incredibly easy to use. Great mobile apps. It's free. Trello keeps track of everything, from the big picture to the minute details.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Asana - Asana project management is an effort to re-imagine how we work together, through modern productivity software. Fast and versatile, Asana helps individuals and groups get more done.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
TickTick - TickTickis a cross-platform to-do list app & task manager helps you to get all things done and make life well organized.
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost