

OpenText Behavioral Signals and Devo compete in data analytics and signal processing. OpenText Behavioral Signals has an advantage in sentiment analysis and emotion recognition, while Devo stands out for its comprehensive data integration and real-time processing features.
Features: OpenText Behavioral Signals provides advanced emotion detection, sentiment analysis, and insightful behavioral analytics. Devo is equipped to handle large-scale data, offers real-time analytics, and is ideal for extensive data integration needs.
Room for Improvement: OpenText Behavioral Signals could enhance its scalability, expand data integration capabilities, and improve user interface intuitiveness. Devo may benefit from refining its training materials, reducing deployment complexity, and enhancing alert customization.
Ease of Deployment and Customer Service: OpenText Behavioral Signals ensures straightforward deployment with integration-focused support, beneficial for tailored implementations. Devo’s deployment strategy is designed for quick, scalable solutions with dedicated customer service, aiding clients through complex environments.
Pricing and ROI: OpenText Behavioral Signals involves higher setup costs but targets long-term analytics value. Devo offers competitive pricing and strong ROI, attributed to efficient data processing and rapid deployment, appealing to organizations needing immediate data solutions.
I rate the customer support a nine out of ten because of their timely technical guidance and responsiveness during the deployment and troubleshooting periods.
Devo is a unified SIEM solution designed to handle growing log volumes and enterprise-scale monitoring requirements.
It is stable and reliable for our security operations.
UI improvements, a simplified dashboard, or an easier reporting workflow could further improve analyst productivity.
Integrations with other sandboxes could be improved to better interpret data using AI and machine learning models.
The cost is a little higher compared to other tools such as DataDog or Elasticsearch, so they could work on reducing costs.
When the analyst uses queries to search, it pulls the data quickly, in a second, which aids us greatly with the investigation.
It utilizes 400 days of hot data, allowing queries to run very fast and yield results quicker than other tools in terms of security and SIEM capability.
When they see a spike in a line chart for a failed login, which could be a true or false attempt, they can click that spike, and a table widget on the same active board instantly populates with raw logs of data for those specific failed logins.
| Product | Mindshare (%) |
|---|---|
| Devo | 1.2% |
| OpenText Behavioral Signals | 0.9% |
| Other | 97.9% |

| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 5 |
| Large Enterprise | 12 |
Devo offers powerful visual analytics, real-time data querying, and log integration capabilities within a cloud-native, multi-tenant architecture, supporting extended data retention ideal for long-term analysis and compliance.
Devo is recognized for its Activeboards, which facilitate visual analytics. High-speed search capabilities and real-time analytics enable efficient data manipulation and querying. Its multi-tenant architecture supports effective data segregation and customization tailored to distinct business needs, enhancing its value for handling complex log integrations. With extended data retention of 400 days and a cloud-native architecture, Devo is a robust platform for long-term analysis and compliance requirements. Though opportunities exist to improve browser stability on large searches, SOAR integrations, and its parser capabilities, Devo remains essential for incident response and security monitoring, offering centralized data storage and analysis.
What are Devo's most important features?Devo is extensively used in industries focused on incident response and digital forensics, centralizing data for security monitoring across hybrid environments. Organizations benefit from its ability to store and analyze aggregated logs, creating alerts and dashboards to enhance visibility for network and endpoint activities in multi-domain settings.
OpenText Behavioral Signals enhances organizational security monitoring with its robust correlation engine and streamlined dashboard, offering customization to suit different environments like airports or banks.
OpenText Behavioral Signals effectively integrates device logs through its strong correlation engine. The platform's customization options enable tailored alerts to match specific use cases, such as airports or banks. Although it needs more frequent updates to stay aligned with global incidents, it provides a centralized dashboard that ensures comprehensive visibility across networks. Users find the interface intuitive, making rule writing and report access easy, aiding in a comprehensive understanding of the network environment.
What are the key features of OpenText Behavioral Signals?In industries like banking and airports, OpenText Behavioral Signals is implemented for gathering global intelligence from the cloud. It notifies organizations about global attacks and updates its correlation engines. These industries utilize the platform for monitoring and analyzing logs from network devices, security log management, and addressing network challenges like link failures and unauthorized login attempts, ensuring better security posture with behavioral analytics and log integration using Unix and Microsoft-based connectors.
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