
Iris provides integration-ready identity and cyber protection solutions that help organizations add powerful customer security capabilities directly into their existing products — without building from scratch. Designed for modern digital platforms, Iris makes it easy to embed identity protection into apps, portals, and customer experiences at scale.
Identity Protection API
Iris’ API suite delivers a multitude of protection solutions—including dark web monitoring & alerts, credit services, risk assessment tools, device protection, and more—into your platform. Teams can fully control the user experience, data flows, and customer journeys while leveraging Iris’ underlying technology and data aggregation.
Micro-Experiences
Prebuilt, customizable UI components that can be embedded directly into your application. These lightweight modules allow teams to quickly deploy identity protection features — such as alerts, dashboards, and monitoring tools — with minimal development effort.
Built for flexibility, Iris supports multiple integration approaches, enrollment methods, and data handling models, so organizations can choose how information flows between users, their systems, and Iris. The platform is designed to scale across large user bases while maintaining strong security and performance standards.
By making identity protection a native part of the user experience, Iris helps organizations increase engagement, strengthen trust, and deliver meaningful, always-on protection to their customers.
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RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
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InfluxDB
InfluxDB is a purpose-built data platform designed to handle all time series data, from users, sensors, applications and infrastructure — seamlessly collecting, storing, visualizing, and turning insight into action. With a library of more than 250 open source Telegraf plugins, importing and monitoring data from any system is easy.
InfluxDB empowers developers to build transformative IoT, monitoring and analytics services and applications. InfluxDB’s flexible architecture fits any implementation — whether in the cloud, at the edge or on-premises — and its versatility, accessibility and supporting tools (client libraries, APIs, etc.) make it easy for developers at any level to quickly build applications and services with time series data.
Optimized for developer efficiency and productivity, the InfluxDB platform gives builders time to focus on the features and functionalities that give their internal projects value and their applications a competitive edge.
To get started, InfluxData offers free training through InfluxDB University.
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Kapacitor
Kapacitor serves as a dedicated data processing engine for InfluxDB 1.x and is also a core component of the InfluxDB 2.0 ecosystem. This powerful tool is capable of handling both stream and batch data, enabling real-time responses through its unique programming language, TICKscript. In the context of contemporary applications, merely having dashboards and operator alerts is insufficient; there is a growing need for automation and action-triggering capabilities. Kapacitor employs a publish-subscribe architecture for its alerting system, where alerts are published to specific topics and handlers subscribe to these topics for updates. This flexible pub/sub framework, combined with the ability to execute User Defined Functions, empowers Kapacitor to function as a pivotal control plane within various environments, executing tasks such as auto-scaling, stock replenishment, and managing IoT devices. Additionally, Kapacitor's straightforward plugin architecture allows for seamless integration with various anomaly detection engines, further enhancing its versatility and effectiveness in data processing.
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