Best Anomaly Detection Software for Apache Kafka
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Compare the Top Anomaly Detection Software that integrates with Apache Kafka as of July 2025
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This a list of Anomaly Detection software that integrates with Apache Kafka. Use the filters on the left to add additional filters for products that have integrations with Apache Kafka. View the products that work with Apache Kafka in the table below.
What is Anomaly Detection Software for Apache Kafka?
Anomaly detection software identifies unusual patterns, behaviors, or outliers in datasets that deviate from expected norms. It uses statistical, machine learning, and AI techniques to automatically detect anomalies in real time or through batch analysis. This software is widely used in cybersecurity, fraud detection, predictive maintenance, and quality control. By flagging anomalies, it enables early intervention, reduces risks, and enhances operational efficiency. Advanced versions offer customizable thresholds, real-time alerts, and integration with analytics dashboards for deeper insights. Compare and read user reviews of the best Anomaly Detection software for Apache Kafka currently available using the table below. This list is updated regularly.
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1
Netdata
Netdata, Inc.
The open-source observability platform everyone needs! Netdata collects metrics per second and presents them in beautiful low-latency dashboards. It is designed to run on all of your physical and virtual servers, cloud deployments, Kubernetes clusters, and edge/IoT devices, to monitor your systems, containers, and applications. It scales nicely from just a single server to thousands of servers, even in complex multi/mixed/hybrid cloud environments, and given enough disk space it can keep your metrics for years. KEY FEATURES: 💥 Collects metrics from 800+ integrations 💪 Real-Time, Low-Latency, High-Resolution 😶🌫️ Unsupervised Anomaly Detection 🔥 Powerful Visualization 🔔 Out of box Alerts 📖 systemd Journal Logs Explorer 😎 Low Maintenance ⭐ Open and Extensible Try Netdata today and feel the pulse of your infrastructure, with high-resolution metrics, journal logs and real-time visualizations.Starting Price: Free -
2
Edge Delta
Edge Delta
Edge Delta is a new way to do observability that helps developers and operations teams monitor datasets and create telemetry pipelines. We process your log data as it's created and give you the freedom to route it anywhere. Our primary differentiator is our distributed architecture. We are the only observability provider that pushes data processing upstream to the infrastructure level, enabling users to process their logs and metrics as soon as they’re created at the source. We combine our distributed approach with a column-oriented backend to help users store and analyze massive data volumes without impacting performance or cost. By using Edge Delta, customers can reduce observability costs without sacrificing visibility. Additionally, they can surface insights and trigger alerts before data leaves their environment.Starting Price: $0.20 per GB -
3
Elastic Observability
Elastic
Rely on the most widely deployed observability platform available, built on the proven Elastic Stack (also known as the ELK Stack) to converge silos, delivering unified visibility and actionable insights. To effectively monitor and gain insights across your distributed systems, you need to have all your observability data in one stack. Break down silos by bringing together the application, infrastructure, and user data into a unified solution for end-to-end observability and alerting. Combine limitless telemetry data collection and search-powered problem resolution in a unified solution for optimal operational and business results. Converge data silos by ingesting all your telemetry data (metrics, logs, and traces) from any source in an open, extensible, and scalable platform. Accelerate problem resolution with automatic anomaly detection powered by machine learning and rich data analytics.Starting Price: $16 per month -
4
InsightFinder
InsightFinder
InsightFinder Unified Intelligence Engine (UIE) platform provides human-centered AI solutions for identifying incident root causes, and predicting and preventing production incidents. Powered by patented self-tuning unsupervised machine learning, InsightFinder continuously learns from metric time series, logs, traces, and triage threads from SREs and DevOps Engineers to bubble up root causes and predict incidents from the source. Companies of all sizes have embraced the platform and seen that business-impacting incidents can be predicted hours ahead with clearly pinpointed root causes. Survey a comprehensive overview of your IT Ops ecosystem, including patterns, trends, and team activities. Also view calculations that demonstrate overall downtime savings, cost of labor savings, and number of incidents resolved.Starting Price: $2.5 per core per month -
5
Acryl Data
Acryl Data
No more data catalog ghost towns. Acryl Cloud drives fast time-to-value via Shift Left practices for data producers and an intuitive UI for data consumers. Continuously detect data quality incidents in real-time, automate anomaly detection to prevent breakages, and drive fast resolution when they do occur. Acryl Cloud supports both push-based and pull-based metadata ingestion for easy maintenance, ensuring information is trustworthy, up-to-date, and definitive. Data should be operational. Go beyond simple visibility and use automated Metadata Tests to continuously expose data insights and surface new areas for improvement. Reduce confusion and accelerate resolution with clear asset ownership, automatic detection, streamlined alerts, and time-based lineage for tracing root causes. -
6
Validio
Validio
See how your data assets are used: popularity, utilization, and schema coverage. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Find and filter the data you need based on metadata tags and descriptions. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Drive data governance and ownership across your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Automatically generated field-level lineage map to understand the entire data ecosystem. Anomaly detection learns from your data and seasonality patterns, with automatic backfill from historical data. Machine learning-based thresholds are trained per data segment, trained on actual data instead of metadata only.
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