
Hadapt
Cloud-optimized system offering an analytical platform for performing complex analytics on structured and unstructured data.
Date | Investors | Amount | Round |
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investor | €0.0 | round | |
investor investor investor | €0.0 | round | |
N/A | €0.0 | round | |
investor | €0.0 | round | |
N/A | - | ||
Total Funding | 000k |
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Hadapt emerged from academic research at Yale University, commercializing in 2011 to address the growing complexities of big data analytics. The company was founded by Dr. Daniel Abadi, a Yale computer science professor, along with Ph.D. student Kamil Bajda-Pawlikowski and Yale School of Management student Justin Borgman. The foundation of Hadapt was the HadoopDB research project, a concept developed by Abadi and Bajda-Pawlikowski that explored creating a hybrid architecture combining the scalability of MapReduce and the performance of parallel database systems. Borgman, as CEO, recognized the commercial potential of this research, leading to the trio leaving their graduate programs and academic posts to establish the company.
Hadapt developed an adaptive analytical platform designed to unify structured and unstructured data analysis. The core of its business was to provide a single platform that integrated the capabilities of standard SQL with the open-source Apache Hadoop framework. This allowed clients, ranging from small to enterprise-sized companies in sectors like financial services and online advertising, to perform complex analytics on massive, diverse datasets without the need for separate systems and connectors. The platform enabled users to leverage familiar BI tools, such as Tableau, for interactive querying and data visualization on top of Hadoop. Revenue was generated by selling this Platform-as-a-Service (PaaS) solution to businesses seeking to enhance their virtual environments and gain insights from multi-structured data.
The company's product, the Hadapt Adaptive Analytical Platform, offered a novel hybrid storage layer. It stored unstructured data in the Hadoop Distributed File System (HDFS) while managing structured data within a relational database based on PostgreSQL. This architecture was designed to allow for interactive, SQL-based analysis on vast datasets. A key feature was its adaptive query execution, which dynamically managed workloads and provided fault tolerance. To further empower developers and analysts, Hadapt created the Hadapt Development Kit (HDK), enabling the creation of custom analytic functions for tasks like sentiment analysis and predictive modeling. After raising approximately $14.8 million in funding from investors including Bessemer Venture Partners and Norwest Venture Partners, Hadapt was acquired by Teradata in July 2014. The acquisition involved Teradata gaining Hadapt's intellectual property and its experienced engineering team to enhance Teradata's own Unified Data Architecture.
Keywords: Hadapt, Teradata, big data analytics, SQL on Hadoop, adaptive analytical platform, unstructured data, structured data, Justin Borgman, Daniel Abadi, Kamil Bajda-Pawlikowski, Yale University, HadoopDB, data warehousing, business intelligence, parallel database systems, MapReduce, hybrid data management, big data integration, data analytics platform, acquired startup