How Lenses.io uses InfluxDB to build Lenses
Lenses is a Streaming Data Management Platform for Apache Kafka. Lenses supports the core elements of Kafka with a web user interface and vital enterprise capabilities that enable engineering and data teams to query real-time data and to create and monitor Kafka topologies with rich integrations to other systems. Lenses Box, Lenses.io's free offering for the Lenses platform, provides the entire Apache Kafka ecosystem in one Docker command.
Lenses.io realized that for IoT data flows, real-time data ingestion plus immediate queries equals actionable/timely insights. They wanted to use Apache Kafka to build a platform that helps developers boost productivity by providing the tools to build end-to-end IoT data pipelines with just a few lines of SQL code. Apache Kafka is an open source streaming framework with messaging semantics and constitutes a good fit for building IoT systems, particularly when leveraging Kafka Streams API (for processing and analyzing data in motion) and Kafka Connect (to ingest data into Kafka reliably and with fault tolerance).
A typical IoT data flow involves a vast network of sensors publishing data periodically. That flux of information is then processed on the fly to extract patterns, trends, or execute predictions. Those end results and the initial data might be stored for further analysis. As IoT data is times series data, and IoT use cases involve large amounts of timestamped device and sensor data typically arriving at infrequent intervals and massive volumes, Lenses.io's platform required a scalable time series database to store streaming data in real time.
Using InfluxDB to meet its storage needs, Lenses.io built Lenses to be an enterprise and scalable streaming platform that supports the core elements of Kafka with a rich user interface, endpoints and vital enterprise capabilities that enable engineering and data teams to query real-time data and to create and monitor Kafka topologies with rich integrations to other systems. Lenses was built and operated in production systems in various industries (from finance to IoT to retail).
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