As real-time data processing at the edge becomes an increasing necessity, one company that is certain to attract attention is Iguazio and their Enterprise Data Cloud, a data platform that serves and consumes data with real-time analytics. Founded in 2014, this Tel-Aviv-based company seeks to provide a solution for those who require secure and expedient handling of large amounts of data from a variety of sources. Iguazio’s unified solution simplifies management and maintenance for customers who might otherwise need to deploy multiple data platforms and services to tackle this problem.
The platform-as-a-service provides complete data lifecycle management with data movement and maintenance processes automated or simplified through self-service portals or APIs. With Iguazio, customers can feed data from multiple sources into their data platform, query it using analytics, and view in it real-time in dashboards or offload it into the cloud for further processing.
All this is a boon to IoT sensors, cars, stock exchanges, or other enterprises that require data processing and extraction in real-time in order to generate critical actions, such as hazard alerts, that could not be done instantaneously if information were traveling to and from the cloud. In fact, the data platform natively supporting the same APIs used at Amazon but delivering speeds roughly 100 times faster. As more and more content is generated at the edge by IoTs and other devices, we suspect Iguazio will play a key role in the future of data management.
- Funding: $15M Series A
- Founders: Yaron Segev, Asaf Somekh, Yaron Haviv
- HQ: Herzliya, Tel Aviv
- Employees: 60+
- Founded: 2014
- Product: Data Platform
- In-factory, regional, hybrid and public cloud deployment models
- Supports data ingest through a variety of protocols and allows users to read it using a different method from ingest
- Provides real-time IoT event notifications for detected changes/anomalies
- Ingests and automatically aggregates sensor data for IoT events and video streams
- Provides streaming for message queues, time-series, logs and videos
- Scales automatically at enterprise level with fault recovery, upgrades, and capacity planning built in
- Data accessed through standard APIs with built-in fine-grain access control to obtain data from any source with zero coding
- Indexes, tags and catalogs data in realtime, based on user/API content or inputs
- Processes 2 million ops/second/node with under 100 milliseconds latency