François Massot
Building A New On-prem Log Product Datadog -- Coming Soon
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolFrançois Massot is a seasoned software engineer and entrepreneur with 12 years building scalable, cloud-native systems and observability tooling. As co-founder of Quickwit he helped design an open-source, Rust-based search engine that separates compute from object storage and powers users at petabyte scale, touting up to 10x cost savings versus traditional search engines. He combines hands-on backend expertise—demonstrated by contributions to core projects like quickwit-oss/quickwit and the Tantivy search library—with product leadership as former CTO and COO in multiple startups. Now at Datadog he is leading the creation of a new on-prem logs product, bringing deep search and indexing experience to enterprise observability. Based in Paris and trained in applied mathematics from Ecole Centrale, he blends strong algorithmic foundations with a practical bias for cost-effective, operable systems. An underrated strength: he repeatedly turns research-grade ideas into production-ready, open-source software that scales from gigabytes to tens of petabytes.
12 years of coding experience
12 years of employment as a software developer
Applied mathematics, Finance, Applied mathematics, Finance at Ecole centrale de Paris
Stackoverflow
410reputation
13kreached
4answers
5questions
Github Skills (19)
algorithm10
algorithms10
search-engine10
tantivy10
metastore10
data-structure10
query-parser10
parse10
data-structures10
rust10
testing9
aggregations8
google-maps-api6
django-models6
metaprogramming6
Programming languages (12)
Github contributions (5)
quickwit-oss/quickwit
May 2021 - Jan 2023
Cloud-native search engine for observability. An open-source alternative to Datadog, Elasticsearch, Loki, and Tempo.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:4 releases, 1880 reviews, 254 commits in 1 year 8 months
Contributions summary:François primarily focused on implementing features related to the Quickwit metastore and search engine. Their work included fixing issues related to index URI parsing and implementing a new SingleFileMetastoreFactory. They also added functionality for handling document mapping, including default mapper implementations, and contributed to the indexing pipeline.
analyticsrustlog-analyticslog-managementlogging
quickwit-oss/tantivy
Jul 2021 - Oct 2022
Tantivy is a full-text search engine library inspired by Apache Lucene and written in Rust
Role in this project:Back-end Developer
Back-end DeveloperContributions:66 reviews, 26 commits, 28 PRs in 1 year 4 months
Contributions summary:François primarily contributed to the core logic and functionality of the Tantivy search engine library, focusing on improving and optimizing the query parsing and execution. Their work included enhancements to field name validation, improvements to the block wand algorithm for efficient search, and adjustments to the type priority for numerical fields. They also addressed issues related to date histogram aggregation and overall code quality by fixing clippy warnings and other test-related issues.
full-text-searchrustfull-textindexingapache
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