rob-med/awesome-ts-anomaly-detectionList of tools & datasets for anomaly detection on time-series data.
List of tools & datasets for anomaly detection on time-series data.
All lists are in alphabetical order. In the lists, maintaned projects are prioritized vs not mantained. A repository is considered "not maintained" if the latest commit is > 1 year old, or explicitly mentioned by the authors.
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| Name | Language | Pitch | License | Maintained |
|---|---|---|---|---|
| Cuebook's CueObserve | Python3 | Anomaly detection on SQL data warehouses and databases. | Apache-2.0 | ✔️ |
| Yahoo's EGADS | Java | GADS is a library that contains a number of anomaly detection techniques applicable to many use-cases in a single package with the only dependency being Java. | GPL | ✔️ |
| AIStream's flow-forecast | Python | Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting). | GPL-3 | ✔️ |
| Hastic | Python + node.js | Anomaly detection tool for time series data with Grafana-based UI. | GPL | ✔️ |
| Zillow's Luminaire | Python | Luminaire is a python package that provides ML driven anomaly detection and forecasting solutions for time series data. | Apache-2.0 | ✔️ |
| MIDAS | C++ | MIDAS, short for Microcluster-Based Detector of Anomalies in Edge Streams, detects microcluster anomalies from an edge stream in constant time and memory. | Apache-2.0 | ✔️ |
| Orion | Python | Orion is a machine learning library built for unsupervised time series anomaly detection, providing a number of “verified” ML pipelines (a.k.a Orion pipelines) that identify rare patterns and flag them for expert review. | MIT | ✔️ |
| OutlierDetection.jl | Julia | Fast, scalable and flexible Outlier Detection with Julia. | MIT | ✔️ |
| PyOD | Python | PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. | BSD 2-Clause | ✔️ |
| ruptures | Python | Ruptures is a Python library for off-line change point detection. This package provides methods for the analysis and segmentation of non-stationary signals. | BSD 2-Clause | ✔️ |
| EarthGecko Skyline | Python3 | Skyline is a real-time anomaly detection system, built to enable passive monitoring of hundreds of thousands of metrics. | MIT | ✔️ |
| Expedia.com's Adaptive Alerting | Java | Streaming anomaly detection with automated model selection and fitting. | Apache-2.0 | ❌ |
| Arundo's ADTK | Python | Anomaly Detection Toolkit (ADTK) is a Python package for unsupervised / rule-based time series anomaly detection. | MPL 2.0 | ❌ |
| Twitter's AnomalyDetection | R | AnomalyDetection is an open-source R package to detect anomalies which is robust, from a statistical standpoint, in the presence of seasonality and an underlying trend. | GPL | ❌ |
| Lytics' Anomalyzer | Go | Anomalyzer implements a suite of statistical tests that yield the probability that a given set of numeric input, typically a time series, contains anomalous behavior. | Apache-2.0 | ❌ |
| banpei | Python | Outlier detection (Hotelling's theory) and Change point detection (Singular spectrum transformation) for time-series. | MIT | ❌ |
| Ele.me's banshee | Go | Anomalies detection system for periodic metrics. | MIT | ❌ |
| CAD | Python | Contextual Anomaly Detection for real-time AD on streagming data (winner algorithm of the 2016 NAB competition). | AGPL | ❌ |
| Chaos Genius | Python | ML powered analytics engine for outlier/anomaly detection and root cause analysis. | MIT | ❌ |
| Mentat's datastream.io | Python | An open-source framework for real-time anomaly detection using Python, Elasticsearch and Kibana. | Apache-2.0 | ❌ |
| DeepADoTS | Python | Implementation and evaluation of 7 deep learning-based techniques for Anomaly Detection on Time-Series data. | MIT | ❌ |
| Donut | Python | Donut is an unsupervised anomaly detection algorithm for seasonal KPIs, based on Variational Autoencoders. | - | ❌ |
| LoudML | Python | Loud ML is an open source time series inference engine built on top of TensorFlow. It's useful to forecast data, detect outliers, and automate your process using future knowledge. | MIT | ❌ |
| Linkedin's luminol | Python | Luminol is a light weight python library for time series data analysis. The two major functionalities it supports are anomaly detection and correlation. It can be used to investigate possible causes of anomaly. | Apache-2.0 | ❌ |
| Numenta's Nupic | C++ | Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM). | AGPL | ❌ |
| oddstream | R | oddstream (Outlier Detection in Data Streams) provides real time support for early detection of anomalous series within a large collection of streaming time series data. | GPL-3 | ❌ |
| PyOdds | Python | PyODDS is an end-to end Python system for outlier detection with database support. PyODDS provides outlier detection algorithms, which support both static and time-series data. | MIT | ❌ |
| PySAD | Python | PySAD is a streaming anomaly detection framework with various online models and complete set of tools for experimentation. | BSD 3-Clause | ❌ |
| rrcf | Python | Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams. | MIT | ❌ |
| Netflix's Surus | Java | Robust Anomaly Detection (RAD) - An implementation of the Robust PCA. | Apache-2.0 | ❌ |
| NASA's Telemanom | Python | A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missions. | custom | ❌ |
This section includes some time-series software for anomaly detection-related tasks, such as forecasting, generic TS analysis and labeling.
