Cohesity
Cohesity is a unified data management platform providing AI-powered backup, recovery, and security solutions to protect your enterprise data across multi-cloud, on-premises, and edge environments from a single interface.
Dataloop
Dataloop is an enterprise-grade data engine providing an all-in-one platform for data labeling, management, and automation to accelerate the development of production-ready AI applications.
Quick Comparison
| Feature | Cohesity | Dataloop |
|---|---|---|
| Website | cohesity.com | dataloop.ai |
| Pricing Model | Custom | Custom |
| Starting Price | Custom Pricing | Custom Pricing |
| FREE Trial | ✓ 30 days free trial | ✓ 14 days free trial |
| Free Plan | ✘ No free plan | ✘ No free plan |
| Product Demo | ✓ Request demo here | ✓ Request demo here |
| Deployment | ||
| Integrations | ||
| Target Users | ||
| Target Industries | ||
| Customer Count | 0 | 0 |
| Founded Year | 2013 | 2017 |
| Headquarters | San Jose, USA | Herzliya, Israel |
Overview
Cohesity
Cohesity simplifies how you protect and manage your data across fragmented environments. Instead of juggling separate tools for backup, file services, and disaster recovery, you get a single platform that consolidates these functions. You can secure your data against ransomware with immutable snapshots and AI-driven threat detection that alerts you to suspicious activity before it spreads.
The platform helps you reduce storage costs by eliminating redundant data copies and moving inactive data to the cloud. You can also put your backup data to work by running analytics or dev-test workloads directly on the platform. It is designed for mid-to-large enterprises that need to maintain high availability and compliance while managing massive amounts of data across hybrid cloud infrastructures.
Dataloop
Dataloop provides you with a centralized data engine to manage the entire lifecycle of your AI development. You can transform raw data into high-quality training sets using integrated annotation tools, automated workflows, and data management capabilities. The platform is designed to bridge the gap between data engineering and machine learning, allowing your teams to collaborate in a single environment rather than jumping between disconnected tools.
You can automate complex data pipelines using a Python-based SDK and trigger-based functions, which significantly reduces the manual effort required for data preparation. Whether you are working with computer vision, natural language processing, or generative AI, the platform scales to handle massive datasets while maintaining strict quality control through built-in validation and consensus workflows.
Overview
Cohesity Features
- Instant Recovery Recover your virtual machines and databases at scale in minutes to minimize downtime during outages.
- Immutable Snapshots Protect your backup data from being encrypted or deleted by ransomware with read-only architectural safeguards.
- AI Threat Detection Identify anomalies in your data patterns automatically to catch potential cyber threats in real-time.
- SmartFiles Manage your unstructured data efficiently with a software-defined file and object solution that scales limitlessly.
- Global Search Find specific files or objects across your entire global footprint instantly with a Google-like search interface.
- Cloud Integration Extend your local storage to the public cloud for long-term retention or disaster recovery with one click.
Dataloop Features
- Multi-modal Annotation. Label images, videos, audio, and text with specialized tools designed for speed and pixel-perfect accuracy.
- Data Management System. Organize and query your unstructured data at scale using advanced metadata filtering and versioning controls.
- AI-Assisted Labeling. Speed up your annotation process by using pre-trained models to automatically generate initial labels for review.
- Workflow Automation. Build custom data pipelines with a Python SDK to automate data routing, processing, and model triggering.
- Quality Control Tools. Ensure high-quality training data by setting up automated validation tests and multi-annotator consensus tasks.
- Model Orchestration. Deploy and manage your machine learning models directly within the platform to create continuous feedback loops.
Pricing Comparison
Cohesity Pricing
Dataloop Pricing
Pros & Cons
Cohesity
Pros
- Fast recovery times for large-scale virtual environments
- Intuitive user interface simplifies complex management tasks
- Strong deduplication significantly reduces your storage footprint
- Consolidates multiple legacy tools into one platform
Cons
- Initial setup requires significant planning and time
- Premium pricing may be high for smaller budgets
- Learning curve for advanced policy-based automation features
Dataloop
Pros
- Highly flexible Python SDK for custom automation
- Excellent support for complex video annotation tasks
- Centralized management of massive unstructured datasets
- Robust quality assurance and consensus workflows
- Seamless integration between labeling and model deployment
Cons
- Steep learning curve for the automation SDK
- Documentation can be technical for non-developers
- Pricing is not transparent for smaller teams