Anodot vs. Datadog
Anodot autonomously baselines, monitors and correlates 100% of your data and metrics for anomalies in real time, so incidents are detected before they impact your customers and revenue
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Why choose Anodot over Datadog?
Monitors 100% of your data
Why only monitor IT infrastructure and apps—when you can monitor your entire business? Not all impactful issues can be observed through IT and application metrics. Very often, revenue, cost, customer experience and partners issues occur without leaving a trace in the app or infrastructure data. Monitoring and correlating 100% of your data and metrics is the only way to spot these common types of revenue bleeds. Anodot scales to billions of metrics, with no restrictions to data or hardware.
Anodot works autonomously
Anodot automatically selects the most appropriate algorithm for every metric, adapts to changes in metric behavior, and can switch algorithms in case patterns change. There are no limitations on metrics with strong trends and recurring patterns: Anodot’s robust algorithm library is built to autonomously baseline and monitor any type of signal. No need to manually create a monitor or set alert conditions or thresholds: all metrics and dimensions are monitored all the time with the most appropriate alert conditions and algorithms.
Fastest incident detection and correlation
Fast automated detection of correlations is continuously done via Anodot’s patented correlation engine, that works across all data sources, metrics and dimensions to create a complete picture of every incident, including root cause analysis, for lightning-fast resolution. Context-based alerts improve collaboration across business/product/devops teams and enable 15 times faster anomaly detection across the business, cutting incident-related costs by 70%.
A look at Datadog
Datadog is a great observability tool when it comes to collecting IT and APM health data, but it lacks the robust ML-based analysis and automation capabilities offered by Anodot on all of your data. Datadog does offer limited anomaly detection capabilities. However, it requires users to decide when to apply anomaly detection, to what KPI, and at what conditions. Of course, it is humanly impossible to scan thousands of KPIs in order to decide which KPI is eligible for anomaly detection and how it’s best evaluated. For these and other reasons, many companies use Anodot to complement Datadog in the same monitoring stack, supercharging Datadog’s capabilities with Anodot’s monitoring prowess.
Why Anodot is better
Scope of data coverage
Anodot
Anodot simply monitors all your data all of the time. Get visibility into 100% of your data with Anodot: infrastructure, application, revenue, cost, customer experience, digital experience, partners, and more.
Datadog
Datadog has robust infrastructure and application monitoring capabilities, but limited customer and digital experience monitoring, and no revenue and cost monitoring. Datadog data is siloed with a limited view of relationships and dependencies.
Level of monitoring automation
Anodot
With Anodot, 100% of your data is autonomously scanned for anomalies in real time using proprietary AI: Automatic anomaly and outlier detection; Auto-learning of seasonality; Autonomous learning of metric behavior; Automatic selection of optimal model; Sequential adaptive learning of normal behavior; Comprehensive metric and event correlation.
Datadog
Datadog’s bolted-on AI provides few algorithms, basic anomaly and outlier detection, manual correlation and no root cause analysis. With Datadog you need to manually create a monitor for each metric and set fixed alert options such as deviations, algorithm, seasonality, daylight savings, rollup interval, and thresholds for alerting, warning, and recovery.
Time scale & seasonality
Anodot
Anodot monitors each metric at multiple time scales: 1-minute, 5-minute, hourly, daily and weekly. This allows the discovery of a range of slow degrading issues that would otherwise go unnoticed. Additionally, Anodot’s patented seasonality algorithm autonomously detects multiple seasonal patterns in time series data without prior knowledge of seasonal periodicity.
Datadog
Datadog can only monitor each metric using a single time scale: you must set a value between 1 minute and 48 hours for threshold-based alerts, and 15 minutes and 48 hours for anomaly detection. Additionally, when setting your alert conditions with Datadog you need to predefine metric seasonality, which is limited to hourly, daily and weekly.
Noise & false positive reduction
Anodot
Anodot employs sophisticated alert reduction mechanisms to deduplicate alerts and eliminate noise. Anodot parses the anomaly’s direction, delta, duration and other factors to generate a score for each anomaly. This scoring mechanism ensures that only — and all — mission critical incidents receive alerts. False positives, false negatives and alert storms are left behind.
Datadog
Individual Datadog alerts with groups will have notification rollups on by default. Additionally, Datadog recommends users apply several methods that often lead to less noisy, more meaningful alerts, such as: adjusting thresholds, reframing the query using functions, using composite alerts or anomaly or outlier detection modules.
Why Anodot is better
Scope of data coverage
Anodot
Anodot simply monitors all your data all of the time. Get visibility into 100% of your data with Anodot: infrastructure, application, revenue, cost, customer experience, digital experience, partners, and more.
Datadog
Datadog has robust infrastructure and application monitoring capabilities, but limited customer and digital experience monitoring, and no revenue and cost monitoring. Datadog data is siloed with a limited view of relationships and dependencies.
Level of monitoring automation
Anodot
With Anodot, 100% of your data is autonomously scanned for anomalies in real time using proprietary AI: Automatic anomaly and outlier detection; Auto-learning of seasonality; Autonomous learning of metric behavior; Automatic selection of optimal model; Sequential adaptive learning of normal behavior; Comprehensive metric and event correlation.
Datadog
Datadog’s bolted-on AI provides few algorithms, basic anomaly and outlier detection, manual correlation and no root cause analysis. With Datadog you need to manually create a monitor for each metric and set fixed alert options such as deviations, algorithm, seasonality, daylight savings, rollup interval, and thresholds for alerting, warning, and recovery.
Time scale & seasonality
Anodot
Anodot monitors each metric at multiple time scales: 1-minute, 5-minute, hourly, daily and weekly. This allows the discovery of a range of slow degrading issues that would otherwise go unnoticed. Additionally, Anodot’s patented seasonality algorithm autonomously detects multiple seasonal patterns in time series data without prior knowledge of seasonal periodicity.
Datadog
Datadog can only monitor each metric using a single time scale: you must set a value between 1 minute and 48 hours for threshold-based alerts, and 15 minutes and 48 hours for anomaly detection. Additionally, when setting your alert conditions with Datadog you need to predefine metric seasonality, which is limited to hourly, daily and weekly.
Noise & false positive reduction
Anodot
Anodot employs sophisticated alert reduction mechanisms to deduplicate alerts and eliminate noise. Anodot parses the anomaly’s direction, delta, duration and other factors to generate a score for each anomaly. This scoring mechanism ensures that only — and all — mission critical incidents receive alerts. False positives, false negatives and alert storms are left behind.
Datadog
Individual Datadog alerts with groups will have notification rollups on by default. Additionally, Datadog recommends users apply several methods that often lead to less noisy, more meaningful alerts, such as: adjusting thresholds, reframing the query using functions, using composite alerts or anomaly or outlier detection modules.
Get a detailed comparison of Anodot vs. Datadog
KING
70% Incident cost reduction
“Even with our massive dataflow, Anodot has proven that it can seamlessly correlate data accross millions of real-time metrics - alerting us immediately so we can react instantly.”
Nanako Yamagishi
Director of Incident and of Service Operations
Anomaly Score
US10061632B2
Seasonality
US10061677B2
Correlation Technology
US20160210556A1
HD Baseline
at Scale
at Scale
Pending