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Imply
Data Analytics
Imply is a Burlingame, California-based analytics database company built around Apache Druid, an open-source database designed for fast, interactive analytics over real-time streaming data.
$840M
+$19.96
1,266.24%
30 days ago
$1.58
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Imply was founded in 2015 by Fangjin Yang, Gian Merlino, and Vadim Ogievetsky, the original creators of Apache Druid, an open-source analytics database they had developed while working at a previous company to address the challenge of running fast, interactive analytical queries over very large volumes of real-time, continuously streaming data, such as user clickstream data, application performance metrics, or Internet of Things sensor data, use cases that traditional analytics databases, often better suited to periodic batch analysis of relatively static historical data, have historically struggled to support well at scale. Imply's core commercial product provides a fully managed cloud service built on Apache Druid, removing the significant operational complexity of self-managing and scaling Druid infrastructure that many organizations running Druid independently have historically found challenging, given the specialized expertise required to properly configure and operate a distributed analytics database at scale. The company's technology has found particular traction in use cases requiring interactive, sub-second query response times over very large and continuously updating datasets, such as real-time business analytics dashboards, network and infrastructure monitoring applications, and digital advertising analytics platforms that need to analyze enormous volumes of continuously streaming event data with minimal latency between when an event occurs and when it's reflected in analytical queries and dashboards. Imply has positioned Druid and its managed cloud service as particularly well suited to use cases sitting at the intersection of needing both very fast query performance and the ability to handle very large, continuously growing data volumes, a combination that has historically been difficult for either traditional data warehouses, which prioritize broad SQL analytical flexibility over the fastest possible query speed, or simpler real-time streaming systems, which often don't support the same depth of analytical querying, to fully address simultaneously. The company has raised substantial venture funding from investors including Bessemer Venture Partners, Khosla Ventures, and Nexus Venture Partners, competing with other real-time analytics databases including ClickHouse and Rockset.
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