Ariel Shtul is a Staff Scientist and seasoned backend engineer with 7 years of focused experience building and maintaining high-performance data structures for Redis, including significant contributions to RedisBloom, RedisTimeSeries and RediSearch. He has deep C/C++ expertise—rewriting and optimizing Count-Min Sketch implementations, adding time-series aggregations and compression, and integrating low-level libraries like xxhash—balanced by academic collaboration on probabilistic data structures. Based in Tel Aviv, Ariel combines an industrial engineering and MBA background with an MPhil in Philosophy, giving him a rare mix of systems rigor, operational savvy and analytical depth. He’s equally comfortable shipping production-grade modules as he is tightening tests and resolving subtle memory and compiler issues, often improving performance and debuggability behind the scenes.
7 years of coding experience
9 years of employment as a software developer
Scholarship, Industrial Engineering, Scholarship, Industrial Engineering at Brown University
MBA, Operations and Supply Chain, MBA, Operations and Supply Chain at Washington University in St. Louis - Olin Business School
Open R&D Bootcamp, C/C++, Open R&D Bootcamp, C/C++ at InfinityLabs R&D
B.Sc., Industrial Engineering and Management, B.Sc., Industrial Engineering and Management at Technion - Israel Institute of Technology
Master of Philosophy - MPhil, Philosophy, Master of Philosophy - MPhil, Philosophy at The Hebrew University of Jerusalem
Contributions:7 releases, 181 reviews, 213 commits in 3 years 9 months
Contributions summary:Ariel made significant contributions to the `redisbloom/redisbloom` repository, primarily focusing on the Count-Min Sketch (CMS) data structure module for Redis. They rewrote the CMS, implementing features like merging and debugging functionalities, and incorporated various optimizations. The user also added tests, addressed code review feedback, and worked on the integration of the xxhash library.
A query and indexing engine for Redis, providing secondary indexing, full-text search, vector similarity search and aggregations.
Role in this project:
Back-end Developer
Contributions:6 releases, 792 reviews, 841 commits in 3 years 3 months
Contributions summary:Ariel primarily contributed to the implementation of features and improvements in the core functionality of the RedisSearch indexing engine. They focused on enhancing and maintaining the internal workings of the engine, as shown by updates to header files, modifications to aggregation execution, and the resolution of compiler warnings and memory management issues. Furthermore, the user was involved in adding new capabilities like score explanation and integrating new commands for more functionality.
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