Immuta vs Qdrant comparison

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Immuta

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Executive Summary

We performed a comparison between Immuta and Qdrant based on real PeerSpot user reviews.

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.

To learn more, read our detailed Immuta vs. Qdrant Report (Updated: September 2026).

Immuta vs. Qdrant

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Helped 915,341 peers since 2012

Review summaries and opinions

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

Categories and Ranking

Immuta

Ranking in AI Data Analysis

27th

Average Rating

7.6

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

Data Governance (25th), Data Security Posture Management (DSPM) (16th)

Qdrant

Ranking in AI Data Analysis

6th

Average Rating

9.0

Reviews Sentiment

5.4

Number of Reviews

Ranking in other categories

Open Source Databases (5th), Vector Databases (2nd)

Mindshare comparison

As of October 2026, in the AI Data Analysis category, the mindshare of Immuta is 0.4%, down from 4.0% compared to the previous year. The mindshare of Qdrant is 0.4%, down from 2.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AI Data Analysis Mindshare Distribution
Product	Mindshare (%)
Qdrant	0.4%
Immuta	0.4%
Other	99.2%

AI Data Analysis

Featured Reviews

Dibyajyoti Rath

Data Analyst at a consultancy with 10,001+ employees

Centralized access control has secured sensitive data and supports compliant self-service analytics

Immuta is very helpful, but it can be improved in a few areas. The initial setup and policy design can be complex and require a learning curve. The user interface could be more interactive, especially for non-technical users. Policy troubleshooting and debugging could be easier with better visibility into why access was allowed or denied. Performance optimization and deeper integration with more tools could make it even better. Additional improvements would strengthen Immuta further. The documentation and real-world examples would help teams onboard faster. More out-of-the-box policy templates could reduce setup time. Improved policy simulation and testing would help teams understand the impact of changes before applying them. Stronger alerting and monitoring features would help quickly identify access issues. Finally, more end-user training and simplified workflows would make it easier for business users to adopt.

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Pawel Cislo

MLOps Engineer at a tech services company with 501-1,000 employees

Adaptive assistant has delivered faster grounded answers and has reduced token costs significantly

The main limitations I notice come down to developer experience and native features rather than performance. Building hybrid retrieval and fusion pipelines still requires considerable manual orchestration and code. Having more built-in multi-query fusion strategies natively inside Qdrant would be a significant time-saver. Additionally, managing dynamic metadata schemas and tracking index build progress during bulk ingest could be more transparent in the web UI. To make things easier for developers, Qdrant could provide more native tools for managing payload schema evolution over time. As metadata needs change in production RAG systems, updating existing payloads across large collections currently requires custom migration scripts. Built-in schema versioning and simpler automated index testing during CI/CD would make running Qdrant in rapidly evolving production environments even smoother. I rate Qdrant 9 out of 10 because its speed, sub-15 millisecond retrieval, and single-stage payload filtering make it top-tier for production RAG pipelines. I deduct one point mainly for developer experience. Setting up multi-query fusion still requires extra boilerplate code, payload metadata schema updates require custom migration scripts, and real-time visibility into HNSW graph indexing progress during bulk ingest could be improved in the web UI.

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Quotes from Members

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

Pros

"The tool's most valuable feature is restriction."

"All features available are good."

"Immuta has had a very positive impact on our organization, helping us strengthen data security by ensuring sensitive data is only accessible to the right users, simplifying compliance with clear audit trails and consistent policy enforcement, reducing manual access management to save time for data and security teams, and enabling safe self-service analytics so our team can access data faster while still meeting governance and regulatory requirements."

"Instead of manually tagging data, Immuta’s auto-discovery capability identifies sensitive information, such as country labels, gender information, and other personal data."

"What I appreciate the most is its user-friendliness."

"Qdrant is one of the best vector databases out there that is also open source."

"Qdrant has positively impacted my organization by significantly improving our RAG system's latency, cost-efficiency, and accuracy."

"Qdrant has positively impacted my organization mainly by reducing usage costs for AI because in the older system, in order to get the context, we were just dumping everything into the system, which would inflate the cost of the API, whatever AI we were using, such as OpenAI or Claude."

"Qdrant has positively impacted my organization by consuming much less time than building systems through coding."

"Qdrant is a good and scalable vector database, and it is free."

"Qdrant has reduced our response time to less than one second for our 128 KB token sizes, and we are satisfied with that performance."

"We saw a clear return on investment from Qdrant, particularly in the engineering time saved and the empowerment of team members to handle self-service tasks instead of reducing headcount."

"Qdrant is an excellent vector database that anyone would want to use with RAG AI."

More Qdrant pros

Cons

"Immuta is behind in updating upgrades and software releases."

"Immuta is very helpful, but it can be improved in a few areas."

"There is room for improvement in enhancing the monitoring capabilities."

"The implementation process with Immuta was quite challenging, primarily due to issues related to database handling and the syncing of user groups."

"We have had some challenges with their support when we were migrating to the cloud version. We we had some issues, and it took us several attempts to get a proper responses as part of that migration."

"The area for improvement in Qdrant is its clustering capability. 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."

"There can always be improvements needed for Qdrant, but I do not want to add anything at this time."

"One of the key limitations is that Qdrant does not have built-in role-based access control, and while being self-hosted is a benefit, it can also be improved."

"A lot of our work is agentic right now, and we have also segmented the content to be logical, so there's not a lot of vector search anymore."

"The file system lock in Qdrant prevents the API and scripts from hitting it directly, and to surpass this limitation, I have to run Qdrant client as a service, which incurs additional costs for running it continuously, so if something about that could be done, it would be really amazing."

"The main limitations I notice come down to developer experience and native features rather than performance."

"Architectural complexity was a key friction point, as our primary database was set in Supabase, necessitating synchronization of two separate systems for user data, permissions, and states."

"Qdrant is available through a containerized Docker, but a normal deployment in Qdrant is not there, and that can actually be worked out."

More Qdrant cons

Pricing and Cost Advice

"Immuta's pricing is expensive."

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

15%

Construction Company

11%

Manufacturing Company

10%

Computer Software Company

Comms Service Provider

12%

Manufacturing Company

12%

Financial Services Firm

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	2

Questions from the Community

What needs improvement with Immuta?

What is your primary use case for Immuta?

My main use case for Immuta is data governance. In my project, which is a data governance project, I use Immuta as a centralized data access management tool. A specific example of how I use Immuta ...

What advice do you have for others considering Immuta?

My advice for others considering Immuta would be to plan your policies carefully. Think through roles, data sensitivity, and use cases before setup. Invest in training to ensure both technical and ...

What is your experience regarding pricing and costs for Qdrant?

I find Qdrant's pricing and licensing extremely straightforward and cost-effective. The core product is open source under Apache 2.0, so initial experimentation and local integration testing cost n...

What needs improvement with Qdrant?

Qdrant is available through a containerized Docker, but a normal deployment in Qdrant is not there, and that can actually be worked out. That was one aspect I thought about, because I need to have ...

What is your primary use case for Qdrant?

We have a full-fledged RAG system using Qdrant Vector Database, and that is how it has benefited us. For example, we have implemented a techno-commercial evaluator using that, and it is in producti...

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Product Reports

Data Governance

Download Immuta product report

Download Qdrant product report

Overview

Immuta ensures secure, controlled access to sensitive data, excelling in data governance, regulatory compliance, and privacy. Key features include dynamic policy enforcement, fine-grained access control, and seamless integration with diverse data sources. Users report improved operational efficiency and enhanced teamwork.

Immuta

Qdrant is a powerful tool for efficiently organizing and searching large volumes of data. It is particularly useful for tasks such as data indexing, similarity search, and recommendation systems.

With fast and accurate results, it is suitable for various applications including e-commerce, content management, and data analysis. Users appreciate Qdrant's efficient search capabilities, high performance, and ease of use.

Its quick and accurate retrieval of relevant information allows for easy navigation and analysis of large datasets.

The intuitive interface and straightforward setup process make it accessible to users with varying levels of technical expertise.

Sample Customers

Information Not Available

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

Immuta vs. Qdrant