

BigID Next and erwin Data Modeler compete in the field of data management and governance. BigID Next appears to have the upper hand due to its strong data scanning and classification capabilities, which are crucial for compliance and data governance.
Features: BigID Next is known for its ability to manage and protect sensitive data with robust scanning and data classification features. It provides integration and automation capabilities, offering comprehensive data visibility across complex environments and ensuring strict data governance. erwin Data Modeler stands out for its visual representation of databases, strong reporting, and data lineage features, which help in team collaboration and communication across business units. It enhances utility through synchronizing and comparing data models in complex environments.
Room for Improvement: BigID Next can enhance areas like file visibility, user interface navigation, and expand its security and automation features. Support for newer database systems and improved classification options is needed. erwin Data Modeler faces challenges with its outdated user interface and compatibility with emerging databases, and users desire better performance with larger models and improved reporting.
Ease of Deployment and Customer Service: BigID Next offers flexible deployment options, including private and hybrid cloud configurations, catering to diverse infrastructure needs, and provides responsive customer service, though problem resolution can be delayed. erwin Data Modeler is mainly deployed on-premises, lacking flexibility for cloud-oriented environments, but shows consistent and reliable customer support, aiding users effectively.
Pricing and ROI: BigID Next is expensive but offers modular pricing that allows purchasing necessary components, optimizing costs for larger companies. Despite the high cost, it provides good ROI in compliance and data management efficiencies. erwin Data Modeler also has a high price, justified by its comprehensive feature set. Its concurrent licensing model suits organizational use, though it's costly. Users find favorable ROI due to streamlined database management and data modeling tasks.
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 three engineers save ten hours each per month using erwin Data Modeler versus manual modeling, that equals three hundred sixty hours saved per year.
It replaces manual charting in Visio with a structured tool, providing significant return on investment.
If the modeling is compromised, then the entire structure will be compromised.
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.
The quality and speed of their support are excellent; everyone is very helpful, and they can solve problems quickly.
This rating reflects my ability to effectively utilize the tool and get support for licensing issues, installation errors, or corrupted repositories end-to-end.
Quest is committed to keeping the product robust.
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.
I would rate it probably a nine, making it a leader in data modeling.
erwin Data Modeler had a very good standardization infrastructure and supported a controlled multi-user environment with check-ins and check-outs.
Performance can degrade during larger collaborations and requires tuning for optimal performance.
BigID is generally stable, however, there is a noted issue with bulk tagging that can affect scan results.
This lack of an auto-save methodology can be improved so that if a system crash occurs, work can be saved and rework can be avoided.
New versions often introduce enhanced features but may cause model crashes due to memory exhaustion.
Sometimes when I want to open the attribute editor, it stops working and the whole application freezes.
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.
The previous version of erwin Data Modeler used to crash unaccountably, but this one hasn't ever crashed on me, so it's been a lot more stable than the previous version that we had.
There are many features, and I would expect good documentation detailing each feature, including when and how to use it, to be very useful because data modeling is not very popular in the data area and there aren't many educational videos regarding erwin Data Modeler.
Erwin Data Modeler could improve in areas such as the interface, as there are features like copy and paste, creating duplicates, and the visualization elements and toolbars which feel quite old.
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.
For a cloud or SaaS standard edition, it typically runs around two hundred to two hundred ninety-nine US dollars per month.
It is more targeted toward an enterprise level since organizations looking to store business information and relationship values may consider the pricing.
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.
One of the key aspects of data governance is defining the data dictionary and clearly identifying which data is accessible by whom and what is not accessible, particularly regarding PII-related data.
The way the data is organized and you have a visual of that organization helps a great deal in terms of trying to remember what you did and trying to retrieve the information.
Migrating DDLs using erwin Data Modeler is easy because I just connect to the database and generate the data model from what is already implemented, making the process straightforward.
| Product | Mindshare (%) |
|---|---|
| BigID Next | 4.9% |
| erwin Data Modeler | 0.4% |
| Other | 94.7% |


| Company Size | Count |
|---|---|
| Small Business | 5 |
| Large Enterprise | 11 |
| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 3 |
| Large Enterprise | 38 |
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.
Erwin Data Modeler provides an effective approach to visualizing and managing data models. It assists in creating, reversing, and synchronizing data models with ease, supporting logical and physical transitions while enhancing understanding across teams.
Erwin Data Modeler is a comprehensive tool designed for professional database management. It offers capabilities to organize and enforce standards, automating script generation with robust reverse engineering and DDL output. Users can manage complex data environments, capitalize on integration with data intelligence, and maintain large-scale databases smoothly. Despite its strengths, improvements in multi-language support, database integration, and reporting features are needed. Users benefit from extensive support for conceptual, logical, and physical database modeling, enhancing architectural design and data governance for platforms like SQL Server, Oracle, and Teradata.
What are the key features of Erwin Data Modeler?Erwin Data Modeler finds application in industries focused on robust data management, implementing it for enterprise data warehouses, business domain models, and operational systems. It supports architectural design and governance, aligning with business applications demanding precise data representation and visualization.
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