StarTree
StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment.
StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark.
StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.
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Epicor Connected Process Control
Epicor Connected Process Control provides a simple-to-use software solution that allows you to configure digital work instructions and enforce process control. It also ensures that operations are error-proof. Connect IoT devices to collect 100% time studies and process data, images and images at the task level. Real-time visibility and quality control on a new level! eFlex can handle any number of product variations or thousands of parts, whether you are a component-based or model-based manufacturer. Work instructions can be linked to Bill of Materials, ensuring that products are built correctly every time, even if changes are made during the process. Work instructions that are part a system that is advanced will automatically react to model and component variations and only display the right work instructions for what's currently being built at station.
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Informatica Data Engineering Streaming
Informatica's AI-driven Data Engineering Streaming empowers data engineers to efficiently ingest, process, and analyze real-time streaming data, offering valuable insights. The advanced serverless deployment feature, coupled with an integrated metering dashboard, significantly reduces administrative burdens. With CLAIRE®-enhanced automation, users can swiftly construct intelligent data pipelines that include features like automatic change data capture (CDC). This platform allows for the ingestion of thousands of databases, millions of files, and various streaming events. It effectively manages databases, files, and streaming data for both real-time data replication and streaming analytics, ensuring a seamless flow of information. Additionally, it aids in the discovery and inventorying of all data assets within an organization, enabling users to intelligently prepare reliable data for sophisticated analytics and AI/ML initiatives. By streamlining these processes, organizations can harness the full potential of their data assets more effectively than ever before.
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AWS IoT
There are countless devices operating in various environments such as residences, industrial sites, oil extraction facilities, medical centers, vehicles, and numerous other locations. As the number of these devices continues to rise, there is a growing demand for effective solutions that can connect them, as well as gather, store, and analyze the data they generate. AWS provides a comprehensive suite of IoT services that span from edge computing to cloud-based solutions. Unique among cloud providers, AWS IoT integrates data management with advanced analytics capabilities tailored to handle the complexities of IoT data seamlessly. The platform includes robust security features at every level, offering preventive measures like encryption and access control to safeguard device data, along with ongoing monitoring and auditing of configurations. By merging AI with IoT, AWS enhances the intelligence of devices, allowing users to build models in the cloud and deploy them to devices where they operate twice as efficiently as comparable solutions. Additionally, you can streamline operations by easily creating digital twins that mirror real-world systems and conduct analytics on large volumes of IoT data without the need to construct a dedicated analytics infrastructure. This means businesses can focus more on leveraging insights rather than getting bogged down in technical complexities.
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