An exabyte-scale, edge-to-cloud data platform for the diverse data needs of Industrial-IoT enterprise applications.
Businesses are actively developing strategies to leverage data, analytics, and artificial intelligence ( AI) capabilities.
At the same time, there is a significant change in infrastructure strategies, with the introduction of hybrid cloud and Kubernetes containerization at unimaginable rates.
This path is a multi-step process along the way with several different critical choices. The BEARTELL Pole Position Data Platform ingests, stores and manages data on a large scale to make new computational techniques and resources readily accessible. The BEARTELL Pole Position Data Platform integrates with the Kubernetes Platform and allows Kubernetes to deploy data-driven applications at scale.
1. Supports a variety of data from large to small, organized and unstructured, in tables, streams, or directories, Internet of Things ( IoT), and sensor data, including a variety of ingestion mechanisms, virtually every type of data from any data source.
2. Supports various tools and systems for computing, such as Hadoop , Spark, ML, TensorFlow, PyTorch, H2o.ai, Sklearn and Caffe.
3. Runs AI and analytics applications concurrently, without having different clusters or silos, meaning quicker time-to-market, fewer maintenance engineering, and more reliable performance, because data scientists and analysts use the same data collection.
4. Offers a wide variety of open-ended APIs POSIX, HDFS, S3, JSON, HBase, Kafka, REST.
5. For all data-in-motion from any data source, like IoT sensors, it provides pub-sub streaming and edge first.
6. Provides reliability , safety and scale to function in global, mission-critical AI and analytic applications for development.
7. Easens data and device movement with Kubernetes between on-premises and in-cloud stateful application support.
8. A vital must-have operates on any cloud, so that a customer can enjoy cloud economy and no cloud lock-in across many public clouds.
9. Enables a global data fabric to consume, store, handle, process, apply and analyze data at once.