Apify is a JavaScript & Node.js based data extraction tool for websites that crawls lists of URLs and automates workflows on the web. With Apify you can manage and automatically scale a pool of headless Chrome / Puppeteer instances, maintain queues of URLs to crawl, store crawling results locally or in the cloud, rotate proxies and much more.
Based on our record, Apify should be more popular than Google Cloud Dataflow. It has been mentiond 21 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.
In this article, I will walk you through everything, from crafting your initial scraping script (Actor) using the Apify SDK for TypeScript to deploying it to the Apify Actors Store for seamless data collection, and then, I will show you how to run your deployed Actor on the Apify platform. With Apify, you don't need to be a programming pro to harness the power of web scraping and start gaining insights. - Source: dev.to / 4 months ago
I am surprised nobody mentioned https://apify.com/ and they even offer discount for YC startups as ex-graduate from the YC Combinator program. - Source: Hacker News / 4 months ago
Web Scraping, Data Extraction and Automation · Apify ( https://apify.com/ ). Source: about 1 year ago
At this point of the tutorial, I'll take the opportunity to do a bit of self-promotion. I'm the COO of Apify, a cloud platform that helps you develop, run, and maintain your web scrapers easily and efficiently. It comes with tons of features like queue storages and proxies, and it supports Puppeteer without any extra configuration. You can run the above scraper, save results and control everything with a powerful... - Source: dev.to / over 1 year ago
Apify a saas that can be helpful in this situation since you can use its api to call actors from your java code. Source: over 1 year ago
Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: over 1 year ago
This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 1 year ago
I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: almost 2 years ago
You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: almost 2 years ago
It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / about 2 years ago
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