Stream analytics software monitors and analyses real-time data integration.

Stream Analytics tools allow users to analyse data that is in transfer between applications or through APIs. This allows users to analyse the sequence of events in real-time. Enterprises use stream analytics to better understand what data users are retrieving to monitor endpoints. However, stream analytics can analyse data being transferred amongst devices like the internet of things (IoT) endpoints, like smart cars, machinery, or home appliances. Many stream analytics contain data visualization components to present and map connected devices. Other common features that stream analytics software platforms encapsulate are competitive analysis and big data analytics. Analytics Insights enlisted the top 10 Stream Analytics software platforms for Data Integration-

Amazon Kinesis

Amazon Kinesis makes it easy to collect, process, and analyse real-time, streaming data such as video, audio, application logs, website clickstreams, and IoT telemetry, so users can get timely insights and react quickly to new information.

TIBCO Spotfire

TIBCO Spotfire® is analytics accelerated, self-service data visualization platform which speeds individual time to insight and analytics adoptions across the enterprise. Spotfire helps users quickly and easily generate insights with three new ways to support their analytical preferences: NLQ powered search, AI-driven recommendations, and direct manipulation wrapped in a streamlined, beautiful interface.

PieSync from Hubspot

PieSync from HubSpot takes care of syncing contacts between the user's favourite cloud apps two-way and in real-time, so they can focus on building their business. PieSync empowers SaaS stack with tailor-made bridges between cloud-based apps.

Azure Event Hubs

Azure Event Hubs is a scalable data streaming platform and event ingestion service, capable of receiving and processing millions of events per second. Event Hubs processes and stores events, data, or telemetry produced by distributed software and devices.

Amazon Elasticsearch Service

Amazon Elasticsearch Service lets users store up to 3 PB of data in a single cluster, enabling them to run large log analytics workloads via a single Kibana interface. Amazon Elasticsearch Service makes it easy to deploy, secure, operate and scale Elasticsearch for log analytics, full-text search, application monitoring, and more.

Lenses

Lenses.io delivers a developer workspace for building & operating real-time applications on any Apache Kafka. By enabling teams to monitor, investigate, secure and deploy on their data platform, organizations can shift their focus to data-driven business outcomes.

Apache Flink

Apache Flink is an open-source stream processing framework for distributed, high-performing, always-available, and accurate data streaming applications.

StreamSets

The StreamSets DataOps platform enables companies to build, execute, operate and protect batch and streaming dataflows. The commercial StreamSets Control Hub is the platform's cloud-native control plane through which enterprises design, monitor and manage complex data movement that is executed by multiple data collectors.

The PI System

The PI System is an enterprise infrastructure for management of real-time data and events with tools and features to help users manage their data.

Conviva

Convivas ecosystem analytics grant visibility to all parties involved in the video delivery process, removing the burden from the video publisher and sharing the responsibility of providing the best quality of experience possible for the consumer.

These top 10 streaming applications and platforms are imperative for enterprises to drive their streaming analytics goals and IoT solutions with ease. While all stream processing platforms can manipulate data while it is in-stream, streaming analytic platforms add to this functionality by providing analytic capabilities critical to a data-driven organisation.