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Lessons Learned From Bigtable Data Migration
(Part 4/4)
March 6, 2020 1:16 am In the previous article, we discussed how we evaluated Cloud Bigtable for Sift, how we prepared our systems for the […]
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Planning a Zero Downtime Data Migration
(Part 3/4)
February 20, 2020 12:49 am In the previous article, we described how we assessed the fitness of Bigtable to Sift’s use cases. The proof of […]
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Evaluating Cloud Bigtable
(Part 2/4)
February 12, 2020 11:08 am In the previous article, we presented the challenges that prompted us to migrate away from HBase on Amazon Web Services […]
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Migrating our cloud infrastructure to Google Cloud
(Part 1/4)
February 12, 2020 10:00 am At Sift, we have built a scalable and highly available technology platform to enhance trust and safety in the digital […]
2017 Sift Engineering in Review
December 31, 2017 4:00 pm2017 has been a pivotal year for Sift Science and the engineering team. We’ve delivered on amazing product launches, technological […]
Running ML Infrastructure on HBase
May 29, 2015 6:52 pmOn May 7th, I presented at HBaseCon, demonstrating how Sift Science leverages HBase and its ecosystem in powering our machine learning infrastructure. In case you missed the talk, I’ll lay out the main points here.There are three main types of events that we receive from customers on our platform: page views (also known as page activities), purchases (also known as transactions), and “labels”.
Running ML Infrastructure on HBase
September 23, 2014 12:59 amWe recently hosted our first ever HBase meetup! This was a very exciting event for us as it was the first time we showed off some of the great infrastructure and systems we've built to power our machine learning platform.