Seif Lotfy is a Berlin-based Co-Founder and CTO with 16 years of experience building cloud-native, high-throughput data platforms. He leads Axiom, a serverless data-insight platform for unlimited machine data, and previously architected horizontally scalable analytics backends at Xamarin and automated OpenStack integrations at Deutsche Telekom. A prolific open-source contributor, his backend work spans InfluxDB and IronFunctions and includes implementations of HyperLogLog++ and a Cuckoo Filter—advancing data integrity, MMAP-backed tooling, performance and bias-correction for cardinality estimation. At Xamarin he leveraged probabilistic data structures to cut query execution to sub-second and O(log n) complexity, turning algorithmic ideas into production speedups. Hands-on and product-minded, he pairs low-level systems plumbing with leadership instincts, and his GitHub motto quietly sums it up: eat, sleep, <code>, repeat.
16 years of coding experience
7 years of employment as a software developer
Bachelor of Science (BSc), Bachelor of Science (BSc) at TU Darmstadt
Contributions:2 reviews, 57 commits, 21 PRs in 6 years 10 months
Contributions summary:Seif primarily focused on implementing and refining a Cuckoo Filter, a data structure. Their work involved setting up the in-memory structure, incorporating methods for insertion, lookup, and deletion. The user also made improvements to the code and documentation. Additionally, they added and refined helper functions and implemented encode and decode functionality.
HyperLogLog with lots of sugar (Sparse, LogLog-Beta bias correction and TailCut space reduction) brought to you by Axiom
Role in this project:
Back-end Developer
Contributions:1 release, 1 review, 75 commits in 4 years 4 months
Contributions summary:Seif primarily focused on implementing core functionalities for the HyperLogLog++ data structure in Go. They initiated the implementation of the `hlltc` package, encompassing the foundational utilities and compressed data structures. The user also introduced marshaling and unmarshaling capabilities, allowing for data persistence and reconstruction. Furthermore, they worked on optimizing the internal registers' behavior and introduced bias corrections for cardinality estimations, improving the accuracy of the data structure.
sparsesugarloglogreductionbias
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