

BigID Next and Cohesity Data Cloud compete in the realm of data management, each with unique offerings. BigID stands out in the areas of pricing and customer support, while users tend to favor Cohesity Data Cloud for its comprehensive features, which they find more valuable relative to the cost.
Features: BigID is renowned for its expertise in data discovery and classification, providing detailed insights into structured and unstructured data. Its proficiency in ensuring compliance and privacy is augmented by advanced machine learning tools for scanning documents across platforms like Google Drive and Azure. In contrast, Cohesity Data Cloud distinguishes itself in backup management, offering NFS and scalable storage solutions coupled with reliable reporting features. Its suite includes disaster recovery support, efficient compression, and deduplication, thereby enhancing overall data protection.
Room for Improvement: BigID has opportunities to fortify its file accessibility and security features, alongside enhancing data classification capabilities. Users express a need for better automation and support for local regulations, with scan reliability and UI navigation pinpointed as critical areas for improvement. Cohesity Data Cloud could improve its documentation and support for multi-tenancy. Connectivity issues, challenges in integrating legacy systems, and competitive pricing also emerge as areas needing attention. Addressing these could improve performance alignment with cloud-based enhancements while handling bandwidth concerns during data transfers.
Ease of Deployment and Customer Service: Both products provide flexible deployment across private, public, and hybrid cloud environments. BigID is commended for its responsive technical support and proactive customer service, albeit with limitations on direct access to higher-tier support for certain subscription levels. Cohesity users value the availability of support teams but note occasional delays in resolution. BigID’s consistent community engagement positively reflects on its support services.
Pricing and ROI: BigID's pricing structure, which links to functionalities and data capacity, is perceived as premium but justifiable due to its robust processing capabilities, delivering notable ROI, particularly in regulatory compliance and mitigating potential penalties. Cohesity Data Cloud, despite its perceived high cost, offers value through effective backup solutions and compliance benefits. Its operational expense model resonates with organizations seeking compliance with minimal upfront costs, offering flexibility through an as-a-service model.
It is one of the best tools in the market.
We have seen returns across all three aspects: fewer employees needed, money saved, and time saved with BigID.
I have seen a return on investment from using BigID, particularly as it is a regulatory and compliance tool that helps avoid potential penalties for non-compliance.
If I find myself stuck in a cyber recovery situation, this tool can help me avoid spending my money on ransom payments.
The level of confidence that Cohesity Data Cloud delivers to the clients is worth that cost.
BigID has one of the best technical support teams.
I would rate the customer support a six because you cannot directly reach out to L3 or L2 support if there's a major issue.
developing the custom connectors was relatively easy because of the courses I attended at BigID University and the support given by the BigID engineering team.
issues with Cohesity Data Cloud have not been encountered, suggesting a robust service.
They need to work faster to meet client requirements, especially when business is affected.
They probably upstaffed and made sure their knowledge was more up-to-date.
I have added very large data sources to the BigID environment, and it remains stable.
BigID is scalable, allowing you to purchase as many scanners as you want.
Scaling depends on subscription levels - when customers exceed their subscribed storage capacity, they can pay Cohesity to scale the resources.
There are no issues with scalability on the cloud end.
It's easy to add additional nodes to a current existing cluster, making it quite easy to expand.
BigID is generally stable, however, there is a noted issue with bulk tagging that can affect scan results.
Compared to other tools, it is very efficient and simple to learn.
I couldn't find anything negative about Cohesity Data Cloud specifically.
Cohesity Data Cloud is quite reliable.
There is also an issue with incident tagging, where all objects get tagged without an option to untag specific ones, and reverting changes is only possible through MongoDB Central, which can lead to data loss for certain periods.
I want them to focus on data mapping, assessment, automation workflow, and privacy incident management.
BigID deserves recognition for the data discovery part, which has been wonderful and quite accurate, along with the confidence level process that allows us to fine-tune results for better accuracy from the database.
Issues such as ransomware protection and fixing vulnerabilities should be prioritized.
Cohesity Data Cloud scans backups by default for ransomware and malware, sending notifications if there are any security concerns or compromised systems.
The primary drawback is the need to transfer large amounts of data to the cloud via an internet connection, requiring significant bandwidth.
BigID might be expensive as it involves various paid services, like data retention and graphic rights management.
The pricing is competitive in the market, however, I need to ask for the right price.
Cohesity Data Cloud is more costly in the long term compared to physical tapes.
Comparatively, compared to IBM and Commvault, Cohesity Data Cloud offers the best deal for my environment.
All organizations are very interested in as-a-service model where they do not pay upfront cost, but they only get the services and pay for what they use as they use it.
One of the best features of BigID is its strength in data discovery and governance.
BigID simplifies things by integrating both data protection and data privacy in one environment, making it easier for end users.
The most valuable feature of BigID is its large number of classifiers, which allow us to scan for specific data such as SSN numbers.
It replicates data to the cloud in a tamper-proof manner, offering protection against ransomware attacks since it is not under administrative control.
They have a feature called DataSock, which enhances data protection.
The initial deployment of Cohesity Data Cloud, from my experience, is easy.
| Product | Market Share (%) |
|---|---|
| BigID | 2.7% |
| Cohesity Data Cloud | 0.6% |
| Other | 96.7% |


| Company Size | Count |
|---|---|
| Small Business | 5 |
| Large Enterprise | 11 |
| Company Size | Count |
|---|---|
| Small Business | 5 |
| Midsize Enterprise | 1 |
| Large Enterprise | 7 |
BigID Next offers advanced data discovery, classification, and governance tools, streamlining compliance with privacy laws while integrating seamlessly with Microsoft platforms.
BigID Next provides comprehensive data management through machine learning-enhanced capabilities, supporting data discovery and classification for both structured and unstructured data. By simplifying processes for GDPR and CCPA compliance, and facilitating data scanning and mapping across databases, it optimizes data management. Automation is central to its design, with solutions for DSAR requests, organizing data with security labels, and ensuring a holistic organizational data view. Improvements in navigation, bug fixes, and scan reliability remain essential, along with enhancing classifiers for broader region coverage.
What features does BigID Next offer?BigID Next is commonly implemented in industries needing robust data governance, such as finance and healthcare, where data privacy and compliance with regulations are critical. It aids in scanning and classifying extensive data volumes, helping businesses maintain regulatory compliance while managing data risks effectively.
Consolidate your backups, file shares, object stores and data for dev/test and analytics on a web-scale data management platform.
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