Zapier
ifttt
Make.com
n8n.io
Boomi
MuleSoft Anypoint Platform
Microsoft Power Automate
Cyclr
Amazon EMR
Google BigQuery
Google Cloud Dataflow
Google Cloud Dataproc
Databricks
Qubole
Snowflake
HortonWorks Data Platform
Zapier Amazon EMRZapier might be a bit more popular than Amazon EMR. We know about 12 links to it since March 2021 and only 10 links to 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.
Indeed, zapier already has this [0] 0 - https://zapier.com/#:~:text=Start%20a%20workflow%20as%20fast%20as%20you%20can%20type. - Source: Hacker News / about 2 months ago
There is some overlap here into the “no-code” or “low-code” world, as sometimes the same teams will hook tools like Zapier up to the BaaS in order to integrate with third parties. For small projects this can lead to superhuman productivity! But over a certain line it can become a mess of complexity where it’s hard to track down where data lives and where it is mutated. - Source: dev.to / 3 months ago
I submitted an application for w24 that fits in the "Developer tools inspired by existing internal tools" category but wasn't accepted. I suspect my pitch probably needed work, and I also haven't started building at all yet and submitted as a solo-founder which it seems has less chance of being accepted. Here's the pitch and some details, in case anyone else is interested in the idea: > Supportal uses AI to... - Source: Hacker News / 3 months ago
Zapier.com — Connect the apps you use to automate tasks. Five zaps every 15 minutes and 100 tasks/month. - Source: dev.to / 4 months ago
Zapier is undoubtedly one of the most popular workflow automation platforms. Its user-friendly interface empowers users, even those without coding knowledge, to create automation workflows known as "Zaps." With an extensive library of integrations, Zapier enables developers to automate repetitive tasks by chaining them together, saving time and effort. - Source: dev.to / 9 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: about 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: almost 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: almost 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
ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Make.com - Tool for workflow automation (Former Integromat)
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
n8n.io - Free and open fair-code licensed node based Workflow Automation Tool. Easily automate tasks across different services.
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost