FiftyOne
5.7#24 in image annotation softwareWebAPILinuxmacOS
VisitFiftyOne vs Label Studio
Label Studio
8.2#2 in image annotation softwareFrom $99 a monthFree planWebAPILinuxmacOS
VisitWhat both publish
| Fact | FiftyOne | Label Studio |
|---|---|---|
| Data handling | The security page states that FiftyOne does not store or transmit datasets and that data remains in the customer's environment. | Input media can remain in external storage and be delivered through presigned URLs, while project settings and annotations are stored in the internal database or configured external stores. |
| Deployment | FiftyOne deployment options include cloud or multi-cloud, hybrid, on-premise, air-gapped, and managed services. | Label Studio can be installed on premises or in the cloud using pip, Docker, Ubuntu, source, or Anaconda. |
| Founded | 2018 | HumanSignal is listed as founded in 2019. |
| Integrations | The official integrations documentation lists annotation integrations including CVAT, Label Studio, V7, and Labelbox, and vector search integrations including Qdrant, Redis, and Pinecone. | The integrations directory lists cloud storage, foundation model APIs, computer vision, speech and audio, ML frameworks, and infrastructure integrations. |
| Purpose | FiftyOne Annotation for images helps identify samples for labeling, automate annotation with AI, and connect labeling with model evaluation. | Label Studio is an open source data labeling tool for labeling multiple data types and connecting machine learning models for predictions or active learning. |
| Security | Voxel51 states that it maintains ISO 27001 certification and undergoes regular third-party penetration and vulnerability tests. | The security documentation says application component interactions use TLS and the web app enforces HTTPS and secured cookies. |
FiftyOne plans
- CustomPriced on request
- GrowthPriced on request
- TeamPriced on request
Label Studio plans
- Community EditionFree
- Starter Cloud$99 a month
- EnterprisePriced on request
Pick FiftyOne if…
It suits AI builders and machine-learning teams working with multimodal data at scale, especially those needing image annotation workflows and model evaluation connections. Its range of deployment options may fit teams with different infrastructure requirements.
Pick Label Studio if…
It suits teams preparing labeled datasets across several media types, from individual community users to organizations needing managed cloud or on-prem deployment. Developers can use its APIs, Python SDK, and webhooks to connect labeling work to other systems.