

Find out in this report how the two AI Data Analysis solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Using Cohesity DataProtect is easier to manage, and it simplifies various components into one architecture, reducing the need for extensive human resources to manage backups.
We have not seen a visual return on investment with Cohesity DataProtect in terms of cash, but when you consider how the software protects and treats your data, we can confirm its value in our environment.
Consequently, we adjusted our processes to use Matillion Data Productivity Cloud only for extraction and ingestion, while Snowflake handled all transformations and jobs.
I would rate the customer support a ten on a scale of 1 to 10.
The support can depend on the region, and for larger customers, I advise having a Technical Account Manager for better assistance.
For the support, I can provide a rating of four only because they initially provide some steps, but later say they are not sure, which is a problem in a production environment.
They communicate effectively and respond quickly to all inquiries.
I have not seen any backup software work with this level of scalability.
Cohesity DataProtect is built on a scale-out architecture, which means it can effectively scale to meet various needs.
Cohesity DataProtect's scalability is quite flexible as you can use one single node or a cluster with many clusters, up to 32 nodes.
Depending on the nature of data sets, volume, and mixture of different data, the scalability could be improved as manual code writing is still required.
The autoscale process works well, allowing the system to start another node automatically if the first machine reaches 80% capacity.
On the whole, any problems were more related to hardware limitations rather than issues with Cohesity DataProtect itself.
Some limitations in virtual environments, we cannot expand to use the software for huge clients.
The container functionality is very limited at the moment, not covering the whole container.
Cohesity DataProtect can be improved by providing backup for all workloads that I know.
The main areas for improvement are AI features and scalability.
Connections to BigQuery for extracting information are complex.
I find Cohesity DataProtect to be expensive.
Matillion Data Productivity Cloud offers discounts and special deals, especially when dealing with high-volume clients or fewer existing clients in specific regions, like Spain.
The pricing is moderate, neither expensive nor cheap.
I appreciate that you have the data protected in each piece and in each other cluster, and it works in protection, allowing the customer to restore the data quickly.
The platform is based on a scale-out architecture with each node having compute, RAM, SSD, and HDD.
The option to maintain evidence in Europe for regulatory compliance, the ability to maintain the backup with the same technology and same control plane, along with the same solutions to use backup solutions such as S3 or similar services in AWS, is what we are working with.
The predefined connectors eliminate the need to write code for connectivity.
Matillion Data Productivity Cloud is effective for ingest functions, particularly when moving information to Snowflake and performing many transformations.
| Product | Mindshare (%) |
|---|---|
| Cohesity DataProtect | 0.4% |
| Matillion Data Productivity Cloud | 0.5% |
| Other | 99.1% |


| Company Size | Count |
|---|---|
| Small Business | 22 |
| Midsize Enterprise | 22 |
| Large Enterprise | 43 |
| Company Size | Count |
|---|---|
| Small Business | 6 |
| Midsize Enterprise | 9 |
| Large Enterprise | 12 |
Cohesity DataProtect integrates with VMware and cloud services like AWS and Azure, offering rapid VM restores and mass recovery, ransomware protection with immutable snapshots, intuitive UI, and scalability. It also consolidates data management, reducing data fragmentation.
Cohesity DataProtect provides comprehensive data protection and management through a user-friendly platform. It offers seamless integration with existing infrastructure, minimizing downtime and maximizing data security. Intuitive features like automated processes, centralized management, and robust search capabilities enhance operational efficiency. Despite areas needing improvement in reporting, interface usability, and legacy support, the platform remains a reliable choice for data backup, recovery, and ransomware protection. Users benefit from its compatibility with VMware, SQL, and Exchange and its ability to replace outdated tape systems while supporting cloud replication and test environments.
What key features does Cohesity DataProtect offer?Cohesity DataProtect is successfully implemented across industries such as finance, healthcare, and education, optimizing data protection and compliance needs. Organizations leverage its robust backup and recovery capabilities, ensuring data integrity and security while facilitating efficient resource use and operation management.
Matillion Data Productivity Cloud offers a user-friendly platform for seamless integration and dynamic data handling, favored for simplifying ETL processes with minimal coding and ensuring robust performance in complex data tasks.
Matillion Data Productivity Cloud integrates effortlessly with platforms like AWS, Snowflake, and SQL databases, providing tools for efficient data migration, transformation, and cloud warehousing. It supports large datasets with swift management, making it valued for its graphical interface that eases ETL processes for non-technical users. Automation features ensure scalability and dynamic data handling across diverse sources, while security and cost-effectiveness enhance its appeal. Enhancements in database connectivity, interface design, and multi-environment support would refine user experience, with growing demands for real-time data capture, SAP connectivity, and frequent API updates.
What are the most important features?In industries like finance, healthcare, and retail, Matillion Data Productivity Cloud is implemented for transforming data operations. Companies leverage it for its speed in data processing and integration capability, facilitating rapid adaptation to data-driven insights crucial in these sectors.
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