GlassFlow

GlassFlow

Open‑source platform for building real‑time Kafka‑to‑ClickHouse data pipelines with built‑in deduplication and joins.

HQ location
Berlin, Germany
Launch date
Employees
Enterprise value
$19—29m
Company register number
HRB 252594 B (Charlottenburg (Berlin))
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DateInvestorsAmountRound
investor investor investor investor investor investor investor investor

€0.0

round
*

€4.4m

Early VC
Total Funding000k
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More about GlassFlow
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GlassFlow is a startup focused on simplifying data streaming for businesses. The company offers a serverless, production-ready solution that allows data teams to build and transform event-based pipelines using Python. This means that instead of spending time on complex infrastructure setups, data engineers can focus on developing machine learning models and other data-driven projects.

GlassFlow primarily serves data engineers and organizations that rely on real-time data processing. These clients span various industries, including e-commerce, where real-time data can significantly enhance operations and customer experiences. The company operates in the data streaming market, which is valued at around $15 billion and is rapidly growing as more businesses seek to leverage real-time data for competitive advantage.

The business model of GlassFlow is likely subscription-based, where clients pay for access to the platform and its features. This model ensures a steady revenue stream while allowing clients to scale their usage based on their needs. GlassFlow makes money by offering a streamlined, efficient way to handle data streaming, which can save companies time and resources, making it a valuable investment.

GlassFlow's mission is to democratize data streaming, making it accessible to data engineers regardless of their background or experience. By simplifying the complexities of data infrastructure, GlassFlow aims to foster a data-driven ecosystem where organizations can thrive through instant insights and innovation.

Keywords: data streaming, serverless, Python, real-time data, data engineers, machine learning, e-commerce, infrastructure, subscription-based, innovation.

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