Data Engineering solutions.
Ingestion, storage and query tooling for high-volume time-series data — built for teams whose own product is a data platform.
Customer projects
InfluxData
A long-standing R&D engineering partnership with InfluxData, building and maintaining tooling for a data ingestion, storage and analytics platform designed around high-volume time-series data — standardized ingestion, a specialized time-series database, and querying, analysis and integration into external systems, exposed through a modular, API-driven design.
Use cases
- High-frequency, high-volume time-series data ingestion via standardized protocols, with batch and asynchronous write paths
- Persistent time-series storage with measurements, tags, fields and timestamps, and configurable retention
- Querying and aggregation over large time-series datasets, including streaming and iterator-based results
- Client libraries and SDKs giving application teams a consistent way to write and query data across languages
- Integration into existing data pipelines and monitoring tools, across cloud-hosted and self-managed deployments
Tech challenges & stack
Sustaining high write throughput and fast query execution under load, while keeping memory use bounded through streaming and chunked processing of large result sets. Retry and backpressure handling for resilient writes, with deterministic, consistent processing behavior even under partial failures. Client libraries maintained across multiple languages — Rust, Go, Java (reactive), and C#/.NET — behind a unified set of API concepts, communicating over HTTP-based APIs and line-protocol writes, with SQL-based and time-series query languages for retrieval, and container-friendly, cloud-ready deployment patterns throughout.