definity is thrilled to announce the general availability of definity, the next-generation Data Application Observability & Remediation solution, purpose-built for Spark-first data platforms.
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Alongside this milestone, definity secured $4.5M in seed funding led by StageOne Ventures, with participation from Hyde Park Venture Partners and an incredible group of current and former founders.
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definity came to life out of our own experiences leading data engineering and product in tech-forward enterprises like Paypal and FIS/Worldpay. definity lived through the day-to-day challenges of data producers, building and maintaining complex data applications (pipelines), and the impact of bad data on data consumers and their customers.
Data engineering today is broken. Over the past decade, data applications have evolved into one of the most mission-critical software in almost every organisation’s technology stack. Yet while application engineers are armed with a robust APM toolset to monitor their applications and infrastructure, pinpoint issues, and quickly resolve downtimes, data engineers are not. They’re forced into a reactive stance, spending more time firefighting than driving new business value.
“Enterprise data engineers demand a new standard of observability that doesn’t exist today,” said Roy Daniel, co-founder & CEO, definity. “Traditional data monitoring focusses on the symptoms, assessing data quality at rest in the data warehouse, which is too out-of-context, reactive, and simply not applicable for Spark. definity fills this void by taking a completely new approach focused on the data application itself, observing in motion how data is processed and how the infrastructure operates, making Spark applications human-readable.”
“Today’s enterprise data leaders face serious pressure to ensure the reliability of the data powering the business while increasing scale, cutting costs, and adopting AI technologies,” said Nate Meir, General Partner, StageOne Ventures. “But without x-ray vision into every data application, data teams are left blind and reactionary. definity is addressing this need head-on with a paradigm-shifting solution that is both powerful and seamless for data engineering and data platform teams.”
The problem is amplified tenfold in the Spark ecosystem, which typically involves heavy and mission-critical workloads and a more obscure infrastructure but lacks modern observability tooling. Altogether, the impact on the business and the data engineering and platform team is significant: data incidents and downtime that lead to direct business loss and customer impact; data engineering capacity waste and low velocity; and skyrocketing infrastructure costs.
definity: The Next-Gen Data Application Observability & Remediation Platform. Spark data engineering teams deserve a better way to ensure the reliability of their data applications, optimise performance, curb infrastructure costs, and prevent data incidents.
About definity
definity is delivering the next-generation data observability solution. It is the industry’s first data application native solution, providing in-motion and contextualised insights into data pipeline execution, data quality, and data infrastructure performance. Using a unique agent-based architecture, definity establishes ubiquitous observability with zero code changes—in on-prem, hybrid, or cloud environments.
