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Upsolver

AI · Tel Aviv-Yafo, Israel · Founded 2014

Upsolver Ltd. operates as a data integration platform that enables organizations to manage and process large-scale data streams in real time. The company was founded in 2014 by Ori Rafael and Yoni Eini, who both possess extensive backgrounds in big data, cloud computing, and algorithmic trading. Rafael, serving as CEO, previously led development for an algo-trading company and specialized in low-latency systems. CTO Yoni Eini's experience includes leading high-performance engineering teams and developing large-scale data processing systems. Their combined expertise in handling massive, high-velocity data sets directly informed the creation of Upsolver. The company's platform is engineered to simplify the complexities of data engineering for cloud environments, particularly for users of Amazon Web Services (AWS) and Snowflake. Upsolver addresses the challenge of building and managing data pipelines that move information from production sources, such as databases and event streams, into analytical repositories like data lakes and data warehouses. This allows businesses to perform analytics on fresh, reliable data without the extensive manual coding and infrastructure management typically required. The platform targets data engineers, data scientists, and developers who need to build scalable and reliable data infrastructure. Upsolver's business model is subscription-based, offering its platform as a service (SaaS) that can be deployed within a customer's own cloud environment, ensuring data remains secure. The service ingests raw data, including structured database information and semi-structured event streams, and transforms it into an analytics-ready format through a declarative SQL-based interface. Key features include automatic schema detection and evolution, data quality monitoring, and the ability to handle both historical and real-time data ingestion efficiently. This functionality empowers organizations to unlock insights from their operational data, enhancing product development and user experiences. The company has secured significant funding, including a $25 million Series B round, to fuel its growth and product development. Keywords: data integration, data pipeline, ETL, cloud data, big data, data engineering, real-time analytics, AWS, Snowflake, data lake