Best Streaming Analytics Platforms for Netdata
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Compare the Top Streaming Analytics Platforms that integrate with Netdata as of July 2025
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This a list of Streaming Analytics platforms that integrate with Netdata. Use the filters on the left to add additional filters for products that have integrations with Netdata. View the products that work with Netdata in the table below.
What are Streaming Analytics Platforms for Netdata?
Streaming analytics platforms are software solutions that enable real-time processing and analysis of data as it is generated or streamed from various sources such as IoT devices, sensors, social media, and transactional systems. These platforms allow businesses to gain immediate insights from continuous data streams, enabling them to make faster decisions, detect anomalies, and optimize operations in real-time. Key features of streaming analytics platforms include data ingestion, real-time event processing, pattern recognition, and advanced analytics like predictive modeling and machine learning integration. They are commonly used in applications such as fraud detection, customer behavior analysis, network monitoring, and supply chain optimization. Compare and read user reviews of the best Streaming Analytics platforms for Netdata currently available using the table below. This list is updated regularly.
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Fluentd
Fluentd Project
A single, unified logging layer is key to make log data accessible and usable. However, existing tools fall short: legacy tools are not built for new cloud APIs and microservice-oriented architecture in mind and are not innovating quickly enough. Fluentd, created by Treasure Data, solves the challenges of building a unified logging layer with a modular architecture, an extensible plugin model, and a performance optimized engine. In addition to these features, Fluentd Enterprise addresses Enterprise requirements such as Trusted Packaging. Security. Certified Enterprise Connectors, Management / Monitoring, and Enterprise SLA-Based Support, Assurance, and Enterprise Consulting Services -
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Apache Flink
Apache Software Foundation
Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams. Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale. Any kind of data is produced as a stream of events. Credit card transactions, sensor measurements, machine logs, or user interactions on a website or mobile application, all of these data are generated as a stream. Apache Flink excels at processing unbounded and bounded data sets. Precise control of time and state enable Flink’s runtime to run any kind of application on unbounded streams. Bounded streams are internally processed by algorithms and data structures that are specifically designed for fixed sized data sets, yielding excellent performance. Flink is designed to work well each of the previously listed resource managers.
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