Multi-API database platform for legacy modernization and edge computing
FairCom is a 45-year-old database company with a narrowly focused product roadmap: modernizing COBOL systems, enabling IoT data collection, and supporting traditional relational workloads via a single engine. The pain-point stack—quality gates blocking releases, defect escape rates, test-coverage gaps—paired with active projects around CI/CD integration and test architecture suggests an engineering org wrestling with backward compatibility at scale. Hiring skews engineering-heavy (6 roles) with only 2 sales positions, typical of a product-led, technical buyer motion in the database space.
FairCom Corporation develops multi-model database technology spanning relational, NoSQL, and embedded use cases. The product portfolio addresses three distinct markets: FairCom DB (JSON-native with ACID guarantees), FairCom RTG (COBOL system modernization without code rewrites), and FairCom Edge (IoT data ingestion and edge compute). The company operates at scale across 100+ countries with a small, distributed team. Primary buyers appear to be enterprises with legacy infrastructure (banking, manufacturing, utilities) and industrial IoT deployments. The technology stack—native COBOL support, Raspberry Pi/edge-device targeting, InfluxDB and Ignition integrations—reflects a dual focus on bridging old systems and enabling new IoT use cases.
FairCom's core is written in C/C++. The platform integrates with InfluxDB, PostgreSQL, and MariaDB for specialized workloads, and uses CMake for build orchestration and CI/CD pipelines for deployment.
Current projects include CI/CD pipeline integration, automated test architecture evolution, core database functionality, performance validation, and a new product for an unspecified new market. Testing infrastructure and release-quality thresholds are central focus areas.
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FairCom Corporation's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.