Avi Avni is a Chief Architect and co-founder of FalkorDB and GraphRAG, combining startup leadership with deep systems engineering expertise in graph databases and compilers. Based in Israel with 10 years of experience, he previously led the RedisGraph team at Redis and contributed performance-critical changes to the F# compiler and core libraries, refactoring list functions and improving parsing and range handling for real-world speed and reliability. A frequent open-source collaborator (dotnet/fsharp, fsprojects/FSharp.Formatting, RedisGraph), he blends C# and F# expertise with practical database internals work—optimizing path algorithms, tuple iterators and cross-platform builds. Neo4j Certified Professional and a hands-on performance engineer, he moves comfortably between high-level architecture and low-level optimizations to ship scalable graph systems.
11 years of coding experience
6 years of employment as a software developer
Softwre development, Softwre development at Sela College
Contributions:461 reviews, 580 commits, 696 PRs in 1 year 6 months
Contributions summary:Avi primarily contributed to the RedisGraph database, focusing on improving core functionality related to the graph database. They refactored tuple iterators, fixed build issues on macOS, and addressed performance concerns. Their work also involved the implementation and optimization of path algorithms and related matrix operations, alongside modifications within edge and node deletion processes.
The F# compiler, F# core library, F# language service, and F# tooling integration for Visual Studio
Role in this project:
Back-end Developer & Performance Engineer
Contributions:3 reviews, 23 PRs, 195 comments in 6 years 7 months
Contributions summary:Avi primarily focused on optimizing the performance of core list functions within the F# core library. They refactored several list functions (like `Sum`, `Max`, `Min`, `Average`, `SumBy`, and `MaxBy`) to utilize more efficient implementations such as `List.fold` and direct iteration, and removed usages of Seq to improve performance. Additionally, the user added and removed performance tests to validate these changes. They implemented unit tests and fixed errors related to the error messages.
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