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BigID Next vs Qdrant comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jan 22, 2026

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
7.3
BigID Next offers strong ROI through compliance, data management integration, cost savings, automation, and reduced staffing, avoiding fines.
Sentiment score
5.2
Qdrant's integration streamlined support ticket resolution, enhancing efficiency and cost-effectiveness through improved retrieval and self-service capabilities.
It is one of the best tools in the market.
Senior Manager at KPMG
We have seen returns across all three aspects: fewer employees needed, money saved, and time saved with BigID.
Senior Security Consultant at a consultancy with 10,001+ employees
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.
Senior Security Consultant at a consultancy with 10,001+ employees
Thanks to Qdrant's open-source nature, our initial licensing and setup costs were nearly zero, allowing for swift testing and launch of our RAG prototype.
Automation Engineer at a educational organization with 11-50 employees
The time saved is substantial, with nearly three weeks or more for projects deployed with Qdrant Cloud in no-code platforms.
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
I have seen a significant return on investment from using Qdrant because it is very easy to integrate and highly efficient, saving a lot of time in my day-to-day operations, which ultimately saves money as well.
Product Engineer at a tech vendor with 11-50 employees
 

Customer Service

Sentiment score
6.5
BigID Next's support is praised for responsiveness, efficiency, and high customer satisfaction, despite occasional delays and time-consuming initial contact.
Sentiment score
5.4
Qdrant's community-driven approach provides ample online resources and documentation, minimizing direct customer support needs and enhancing satisfaction.
BigID has one of the best technical support teams.
Senior Manager at KPMG
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.
Senior Security Consultant at a consultancy with 10,001+ employees
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.
Senior Security Consultant at a consultancy with 10,001+ employees
It's open source, so we house it on our server.
Chief Ai Scientist at Predictive Systems
The documentation provided by Qdrant covers most queries effectively.
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
I rate the technical support of Qdrant as a nine because I think we have never reached out to them directly, but Qdrant has good support available online, and I can get answers from forums.
Co Founder & CEO at SaYukth Private Limited
 

Scalability Issues

Sentiment score
6.7
BigID Next is scalable with mixed opinions, excelling in large environments but facing data handling and presentation challenges.
Sentiment score
5.5
Qdrant's scalability in Docker enables efficient expansion and performance with multiple CPUs, attracting migrations from alternative solutions.
I have added very large data sources to the BigID environment, and it remains stable.
Senior Security Consultant at a consultancy with 10,001+ employees
BigID is scalable, allowing you to purchase as many scanners as you want.
Senior Security Consultant at a consultancy with 10,001+ employees
In the recruiting agency project, the reliance on the vector database has expanded from storing hundreds of resumes to thousands.
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
When Qdrant is deployed in Docker, it scales really fast, and you can assign multiple CPUs to enhance performance.
Analyst at Synergy Connect
Qdrant handles growing workloads and data volumes well for me, which was a significant reason for my shift from other popular alternatives to Qdrant.
Product Engineer at a tech vendor with 11-50 employees
 

Stability Issues

Sentiment score
7.5
BigID Next is often seen as reliable with some stability concerns but praised for data security and ease of use.
Sentiment score
7.7
Qdrant is stable, reliable, easy to use, but inactive clouds terminate after a week, affecting continuous hosting.
BigID is generally stable, however, there is a noted issue with bulk tagging that can affect scan results.
Senior Associate - IT Governance and Compliance at Fulcrum Digital Inc
You need to patch Qdrant as soon as patches are released.
Co Founder & CEO at SaYukth Private Limited
It is easy to use whether on LangChain or on its own.
Product Engineer at a tech vendor with 11-50 employees
Qdrant is stable, except for the limitation concerning the termination of inactive clouds after a week.
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
 

Room For Improvement

BigID Next needs enhancements in file access, security, automation, UI navigation, deployment, data governance, and support features.
Qdrant requires UI enhancements, improved backup management, and integrated automation to address operational complexities and improve features.
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.
Senior Associate - IT Governance and Compliance at Fulcrum Digital Inc
I want them to focus on data mapping, assessment, automation workflow, and privacy incident management.
Senior Manager at KPMG
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.
Assistant Manager - Cyber : Digital Privacy and Trust at Deloitte
Fast large-scale filtering operations could be implemented, such as automatic index suggestions, adaptive query planning, and smart indexing of metadata fields, which would make Qdrant even more efficient.
Product Engineer at a tech vendor with 11-50 employees
While it has clustering functionality, it is not easy to set up, and not everyone can configure the clustering, so there is room for improvement in the clustering configuration.
Co Founder & CEO at SaYukth Private Limited
Incorporating embedding features directly in Qdrant Cloud would eliminate the need to depend on external solutions.
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
 

Setup Cost

BigID Next offers premium, capacity-based pricing; valued by large enterprises for advanced features, less feasible for smaller businesses.
Qdrant offers cost-effective enterprise pricing but scaling may require migrating to paid plans for advanced features and support.
BigID might be expensive as it involves various paid services, like data retention and graphic rights management.
Senior Associate - IT Governance and Compliance at Fulcrum Digital Inc
The pricing is competitive in the market, however, I need to ask for the right price.
Senior Manager at KPMG
Using Qdrant is free.
Chief Ai Scientist at Predictive Systems
Regarding pricing, setup costs, and licensing, since I am using only the free tier of Qdrant Cloud, there are no setup costs involved.
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
Licensing posed no issues, as Qdrant is open-source software with no upfront fees.
Automation Engineer at a educational organization with 11-50 employees
 

Valuable Features

BigID Next offers a user-friendly design, seamless Microsoft integration, and powerful data discovery, classification, and protection capabilities.
Qdrant enhances search precision using hybrid vectors, offers cost-effective deployment, and supports efficient AI handling with flexible APIs.
One of the best features of BigID is its strength in data discovery and governance.
Senior Manager at KPMG
BigID simplifies things by integrating both data protection and data privacy in one environment, making it easier for end users.
Senior Security Consultant at a consultancy with 10,001+ employees
The most valuable feature of BigID is its large number of classifiers, which allow us to scan for specific data such as SSN numbers.
Senior Associate - IT Governance and Compliance at Fulcrum Digital Inc
The ability of Qdrant to handle high-dimensional vectors for my AI projects is pretty fast, and I think it's the best we have used so far.
Chief Ai Scientist at Predictive Systems
An accuracy boost was definitely observed from 45 to 50% using Faiss to around 85 to 95% using Qdrant, and the users are really happy as they are getting suggested really good schemes that would take a lot of time to find.
Analyst at Synergy Connect
The best features of Qdrant are GPU support, which enables very fast processing, and a very light footprint as it uses fewer resources.
Co Founder & CEO at SaYukth Private Limited
 

Categories and Ranking

BigID Next
Ranking in AI Data Analysis
8th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
15
Ranking in other categories
Data Loss Prevention (DLP) (12th), Data Governance (8th), Data Privacy Management Software (1st), Data Security Posture Management (DSPM) (6th)
Qdrant
Ranking in AI Data Analysis
11th
Average Rating
9.0
Reviews Sentiment
5.7
Number of Reviews
6
Ranking in other categories
Open Source Databases (9th), Vector Databases (4th)
 

Mindshare comparison

As of July 2026, in the AI Data Analysis category, the mindshare of BigID Next is 0.8%, down from 23.1% compared to the previous year. The mindshare of Qdrant is 0.4%, down from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Data Analysis Mindshare Distribution
ProductMindshare (%)
BigID Next0.8%
Qdrant0.4%
Other98.8%
AI Data Analysis
 

Featured Reviews

Aniruddha Nath - PeerSpot reviewer
Senior Security Consultant at a consultancy with 10,001+ employees
Data discovery has transformed compliance workflows and automation now speeds up requests and remediation
The best feature that BigID offers is data discovery and classification, which is the most powerful engine. It allows connecting to many different data sources, ranging from cloud to on-premises to structured to unstructured data. If there is no connector available, you can build your own classifiers as well. Regarding the custom classifier option, you can build custom classifiers using regular expressions, and I have done that if you know how to create regular expressions. Custom connectors are something you create to connect to a database where the connector is not available. BigID has positively impacted my organization as it's a very powerful tool, especially with the increasing regulatory compliances for different countries such as GDPR, CCPA, and India's recent DPDPA act. Having these tools in place greatly helps organizations avoid any penal charges for not being compliant with the regulatory compliances. For example, regarding compliance or reduced risks for my clients, the DSAR process I was talking about allows organizations to respond quickly to user data deletion requests under GDPR law, which traditionally has a 30-day or 60-day timeline. In larger organizations, when the number of requests is high, it becomes tedious. However, using DSAR automation with BigID, it's almost instantaneous; instead of 30 days, you can respond in just one day to what users have requested.
Chirag Morajkar - PeerSpot reviewer
Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees
Building accurate no-code resume screeners has saved weeks in document search workflows
I see room for improvement in Qdrant based on what another platform called Weaviate offers. Qdrant provides an excellent vector database with a solid searching method. However, it could elevate its offering by integrating embedding features. Currently, for the workflow automation I build, I rely on other platforms for embedding, so incorporating this feature directly in Qdrant Cloud would eliminate the need to depend on external solutions. A pain point I have encountered was the inactive expiration of the cloud created for certain projects. If the cloud is not used for a week, it gets terminated, which is frustrating. I think increasing that inactivity window in the free tier would be beneficial, as I have faced limitations due to this seven-day inactivity rule, requiring me to reset up the cloud after its termination.
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Top Industries

By visitors reading reviews
Financial Services Firm
20%
Manufacturing Company
10%
Insurance Company
8%
Comms Service Provider
6%
Comms Service Provider
11%
Financial Services Firm
10%
Manufacturing Company
10%
Computer Software Company
10%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business5
Large Enterprise11
By reviewers
Company SizeCount
Small Business8
 

Questions from the Community

What needs improvement with BigID?
One improvement I would suggest is addressing the intermittent failures of BigID scans, as there are times when some errors occur. I think the BigID team is aware of this and works on resolving iss...
What is your primary use case for BigID?
BigID's main use case is connecting to various data sources to perform the data discovery process, classify the data within those systems, and identify sensitive information across various structur...
What advice do you have for others considering BigID?
I have covered information regarding data scanning, data classification, and the DSAR module, as these are the parts I have worked on, apart from developing custom connectors for a few data sources...
What is your experience regarding pricing and costs for Qdrant?
Licensing posed no issues, as Qdrant is open-source software with no upfront fees. Initially, the setup cost was low since we utilized a self-hosted model on a small cloud VM. However, as we added ...
What needs improvement with Qdrant?
While Qdrant is an exceptionally fast and efficient search engine within vector bases, our engineering team faced operational challenges during its adoption. Architectural complexity was a key fric...
What is your primary use case for Qdrant?
I have been using Qdrant for almost one and a half years. This was actually one of the first vector databases that we picked up in our organization. We started using the RAG modules to create a per...
 

Comparisons

 

Overview

 

Sample Customers

Home Depot, Grant Thornton LLP, Cimpress, Fidelity Investments
1. Airbnb 2. Amazon 3. Apple 4. BMW 5.Cisco 6. CocaCola 7. Dell 8. Disney 9. Google 10. HP 11. IBM 12. Intel 13. JPMorgan Chase 14. Kraft Heinz 15. L'Oreal 16. McDonalds 17. Merck 18. Microsoft 19. Nike20. Oracle 21. PG 22. PepsiCo 23. Procter and Gamble 24. Samsung 25. Shell 26. Sony 27. Toyota 28. Visa 29. Walmart 30. WeWork
Find out what your peers are saying about BigID Next vs. Qdrant and other solutions. Updated: June 2026.
902,894 professionals have used our research since 2012.