Anomalib
7.4#2 in anomaly detection softwareFree planFree planWebAPILinuxSelf-hosted
VisitAnomalib vs Soda
What both publish
| Fact | Anomalib | Soda |
|---|---|---|
| Deployment | Inference options include Torch, Lightning, Gradio, and OpenVINO. | Soda offers three deployment models based on infrastructure and data privacy needs. |
| Documentation depth | The documentation includes reference APIs, CLI, data and model guides, inference, metrics, pipelines, tutorials and developer guides. | Public documentation covers quickstarts, YAML contract language, CLI and Python references, data-source connections, architecture and release notes. |
| License | The repository identifies its license as Apache-2.0. | Soda Core changed from Apache 2.0 to Elastic License 2.0 in January 2026; the source remains readable and modifiable but cannot be offered as a competing hosted service. |
| Purpose | Anomalib is a deep learning library for benchmarking, developing, and deploying anomaly detection algorithms, with a focus on detecting or localizing anomalies in images and videos. | Soda is a data quality platform for monitoring data quality, catching problems early, understanding issues at source, and taking action. |
Anomalib plans
- Open-source Anomalib libraryFree
- Open-source libraryFree
Soda plans
- FreeFree
- Team$750 a month
- EnterprisePriced on request
Pick Anomalib if…
Anomalib suits developers building or benchmarking image and video anomaly detection, including those deploying inference on supported hardware. Studio may appeal to users seeking a low/no-code web application, provided they can work with pre-release software.
Pick Soda if…
Soda is aimed at data engineers, data producers and consumers, governance teams, and platform teams who need data checks and observability across workflows.