Re:amaze is a complete customer service and helpdesk platform with all the tools you need to efficiently manage and deliver awesome experiences. Thousands of brands around the world use Re:amaze to help customers on a daily basis using our email, social media, live chat, SMS, VOIP, and FAQ knowledge base features.
With over 800 5-star reviews on Google, G2 Crowd, Alternative-To, Capterra, Crozdesk, Shopify, and BigCommerce, Re:amaze is the winner of G2 Crowd’s Top Performer, Leadership, and Best Experience Awards 3 years running and named as one of the fastest growing SaaS companies in the United States by Latka 100 in 2018.
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Based on our record, Google Cloud Dataflow seems to be a lot more popular than Reamaze. While we know about 14 links to Google Cloud Dataflow, we've tracked only 1 mention of Reamaze. 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.
ABOUT: Full-Stack Software Engineer with 9 years of experience working with companies like Shogun (https://getshogun.com) (YCombinator W18), Re:amaze (https://reamaze.com) (Acq. By GoDaddy), Gametime (https://gametime.co), DigitalClipboard (https://digitalclipboard.com), Ministry of Health of Georgia. - Source: Hacker News / about 3 years 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: over 1 year 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: over 1 year 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 / almost 2 years ago
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