Qdrant vs Redis comparison

Qdrant and Redis are both solutions in the Vector Databases category. Qdrant is ranked #3 with an average rating of 9.0, while Redis is ranked #2 with an average rating of 8.9. Qdrant holds a 6.7% mindshare in VD, compared to Redis’s 6.5% mindshare. Additionally, 100% of Qdrant users are willing to recommend the solution, compared to 100% of Redis users who would recommend it.

Qdrant

Read 6 Qdrant reviews

4,230 Views
3,088 Comparison Views

100% willing to recommend

Redis

Read 26 Redis reviews

8,577 Views
3,088 Comparison Views

100% willing to recommend

Qdrant

Redis

Comparison Buyer's Guide

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Executive SummaryUpdated on Mar 15, 2026

Redis and Qdrant are competitive in the database management category, with Redis having an advantage in general-purpose data operations and performance, and Qdrant having strengths in vector similarity search.

Features: Redis provides high-speed data processing, efficient caching capabilities, and robust data structures. Qdrant is known for advanced vector search algorithms, scalability for AI-driven data, and optimization for AI applications.

Ease of Deployment and Customer Service: Redis benefits from extensive documentation and a strong community support, making deployment smooth. Qdrant offers easy integration with active developer support, though its community resources are less mature.

Pricing and ROI: Redis involves low initial setup costs with strong potential for high ROI due to efficient data handling, while Qdrant might require more investment but offers significant returns in AI and analytics sectors.

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

Buyer's Guide

Qdrant vs. Redis

April 2026

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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

5.2

Qdrant's integration streamlined support ticket resolution, enhancing efficiency and cost-effectiveness through improved retrieval and self-service capabilities.

Sentiment score

7.2

Redis enhances ROI by improving performance, reducing costs, increasing productivity, and ensuring reliable, scalable, and efficient service.

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.

Amrit Dash

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.

Chirag Morajkar

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.

reviewer2848647

Full Stack Product Engineer at a tech vendor with 11-50 employees

For more quotes and insights, download the Qdrant report

It improved API latency from two seconds to 450 milliseconds for P99.

Varuns Ug

Senior Software Developer at NIT

We reduced the database read load by around 30 to 40 percent and improved API response time by 20 to 30 percent, specifically for frequently accessed endpoints.

RituRaj

SDE 2 at Virtusa

For more quotes and insights, download the Redis report

Customer Service

Sentiment score

5.4

Qdrant's community-driven approach provides ample online resources and documentation, minimizing direct customer support needs and enhancing satisfaction.

Sentiment score

5.8

Redis is stable and reliable, with helpful support, strong documentation, and often minimal need for direct assistance.

It's open source, so we house it on our server.

AllanTan1

Chief Ai Scientist at Predictive Systems

The documentation provided by Qdrant covers most queries effectively.

Chirag Morajkar

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.

China Venkanna Varma Ponnamanda

Co Founder & CEO at SaYukth Private Limited

For more quotes and insights, download the Qdrant report

The documentation and community support for Redis are very strong, making troubleshooting quicker.

Varuns Ug

Senior Software Developer at NIT

Since Redis is quite stable and well-documented, we have not needed much support, but when required, the response has been helpful.

RituRaj

SDE 2 at Virtusa

For more quotes and insights, download the Redis report

Scalability Issues

Sentiment score

5.5

Qdrant's scalability in Docker enables efficient expansion and performance with multiple CPUs, attracting migrations from alternative solutions.

Sentiment score

7.8

Redis excels in horizontal and vertical scaling, offering clustering, sharding, and compatibility with Azure and AWS for enterprise adaptability.

In the recruiting agency project, the reliance on the vector database has expanded from storing hundreds of resumes to thousands.

Chirag Morajkar

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.

Vedant Wani

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.

reviewer2848647

Full Stack Product Engineer at a tech vendor with 11-50 employees

For more quotes and insights, download the Qdrant report

Data migration and changes to application-side configurations are challenging due to the lack of automatic migration tools in a non-clustered legacy system.

reviewer2005650

Data Engineer at a photography company with 1,001-5,000 employees

I scale Redis horizontally using clustering and sharding, where data is distributed across multiple nodes to handle higher traffic and larger data sets.

Varuns Ug

Senior Software Developer at NIT

With features such as clustering and replication, it can handle high traffic and a large database very effectively.

RituRaj

SDE 2 at Virtusa

For more quotes and insights, download the Redis report

Stability Issues

Sentiment score

7.7

Qdrant is stable, reliable, easy to use, but inactive clouds terminate after a week, affecting continuous hosting.

Sentiment score

7.8

Redis is stable, handles heavy loads, offers high availability, and uses persistence mechanisms, making it a trusted choice.

You need to patch Qdrant as soon as patches are released.

China Venkanna Varma Ponnamanda

Co Founder & CEO at SaYukth Private Limited

It is easy to use whether on LangChain or on its own.

reviewer2848647

Full Stack 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.

Chirag Morajkar

Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees

For more quotes and insights, download the Qdrant report

Redis is fairly stable.

reviewer2005650

Data Engineer at a photography company with 1,001-5,000 employees

For more quotes and insights, download the Redis report

Room For Improvement

Qdrant requires UI enhancements, improved backup management, and integrated automation to address operational complexities and improve features.

Redis users face challenges with scalability, GUI, documentation, security, and seek enhancements in monitoring, analytics, and multi-tenancy features.

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.

reviewer2848647

Full Stack 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.

China Venkanna Varma Ponnamanda

Co Founder & CEO at SaYukth Private Limited

Incorporating embedding features directly in Qdrant Cloud would eliminate the need to depend on external solutions.

Chirag Morajkar

Lead Ai Tech And Tech Automation Engineer at a individual & family service with 11-50 employees

For more quotes and insights, download the Qdrant report

Data persistence and recovery face issues with compatibility across major versions, making upgrades possible but downgrades not active.

reviewer2005650

Data Engineer at a photography company with 1,001-5,000 employees

Redis itself does not enforce consistency with the primary database, so developers need to carefully design cache invalidation strategies.

Ravi Raushan Kumar

Software Engineer at ValueMomentum

One issue is cache invalidation. Keeping cache data consistent with the source of truth can be tricky, especially in distributed systems.

Varuns Ug

Senior Software Developer at NIT

For more quotes and insights, download the Redis report

Setup Cost

Qdrant offers cost-effective enterprise pricing but scaling may require migrating to paid plans for advanced features and support.

Redis pricing depends on memory, cluster size, and infrastructure, with higher costs than SQL due to RAM usage.

Using Qdrant is free.

AllanTan1

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.

Chirag Morajkar

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.

Amrit Dash

Automation Engineer at a educational organization with 11-50 employees

For more quotes and insights, download the Qdrant report

Since we use an open-source version of Redis, we do not experience any setup costs or licensing expenses.

reviewer2005650

Data Engineer at a photography company with 1,001-5,000 employees

The costs are primarily driven by memory consumption and cluster size, since Redis operates in-memory.

Varuns Ug

Senior Software Developer at NIT

The pricing is reasonable for the performance provided.

RituRaj

SDE 2 at Virtusa

For more quotes and insights, download the Redis report

Valuable Features

Qdrant enhances search precision using hybrid vectors, offers cost-effective deployment, and supports efficient AI handling with flexible APIs.

Redis offers low latency, high throughput, and scalability with rich data structures, ideal for real-time applications and caching.

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.

AllanTan1

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.

Vedant Wani

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.

China Venkanna Varma Ponnamanda

Co Founder & CEO at SaYukth Private Limited

For more quotes and insights, download the Qdrant report

It functions similarly to a foundational building block in a larger system, enabling native integration and high functionality in core data processes.

reviewer2005650

Data Engineer at a photography company with 1,001-5,000 employees

First is its in-memory preference, as Redis is extremely fast, making it ideal for caching and session management where low latency is critical.

Ravi Raushan Kumar

Software Engineer at ValueMomentum

Real API latency improved from around two seconds to approximately 450 milliseconds for P99.

Varuns Ug

Senior Software Developer at NIT

For more quotes and insights, download the Redis report

Categories and Ranking

Qdrant

Ranking in Vector Databases

3rd

Average Rating

9.0

Reviews Sentiment

5.7

Number of Reviews

Ranking in other categories

Open Source Databases (9th), AI Data Analysis (12th)

Redis

Ranking in Vector Databases

2nd

Average Rating

8.8

Reviews Sentiment

5.9

Number of Reviews

Ranking in other categories

NoSQL Databases (3rd), Managed NoSQL Databases (6th), In-Memory Data Store Services (1st), AI Software Development (12th)

Mindshare comparison

As of June 2026, in the Vector Databases category, the mindshare of Qdrant is 6.7%, down from 8.1% compared to the previous year. The mindshare of Redis is 6.5%, up from 4.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Mindshare Distribution
Product	Mindshare (%)
Redis	6.5%
Qdrant	6.7%
Other	86.8%

Vector Databases

Featured Reviews

Chirag Morajkar

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.

Read full review

Varuns Ug

Senior Software Developer at NIT

Caching has accelerated complex workflows and delivers low latency for high-traffic microservices

A few features of Redis that I use on a day-to-day basis and feel are among the best are extremely low latency and high throughput. Since Redis is in-memory, it makes it ideal for cases such as caching and rate limiting where response time is critical. TTL expiry support is very useful in Redis as it allows me to automatically evict stale data without manual cleanup, which is something I use heavily in my caching strategy. Another point I can mention is that the rich data structures such as strings, hashes, and even sorted sets are very powerful. I have used strings for caching responses and counters, whereas I have used hashes for storing structured objects. One more feature I can tell you about is atomic operations. Redis guarantees atomicity for operations such as incrementing a counter, which is very useful for rate limiting and avoiding race conditions in distributed systems. Finally, I want to emphasize that Redis is easy to scale and integrate, whether through clustering or using a distributed cache across microservices. Redis has impacted my organization positively by providing default support that is very useful. For metrics, in one of my core systems, introducing Redis as a distributed cache helped me achieve around an 80% cache hit rate, which reduced repeated downstream services. Real API latency also improved from around two seconds to approximately 450 milliseconds for P99. It also helped reduce the load on dependent services and databases, which improved overall system reliability.

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Top Industries

By visitors reading reviews

Comms Service Provider

11%

Financial Services Firm

11%

Manufacturing Company

10%

Computer Software Company

Financial Services Firm

24%

Computer Software Company

10%

University

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	8

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	6
Large Enterprise	10

Questions from the Community

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 ...

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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...

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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...

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What needs improvement with Redis?

Overall, Redis is a powerful and reliable tool, but there are a few areas for improvement. One limitation is that Redis is memory-based, so scaling can become expensive compared to disk-based syste...

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What is your primary use case for Redis?

My main use case for Redis is caching frequently accessed data to improve performance and reduce database load. For example, I cache API responses and user-related data so that repeated requests ca...

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What advice do you have for others considering Redis?

My main advice for those looking into using Redis is to focus on the use case; Redis excels where low latency is critical, such as caching, session management, or real-time features, rather than us...

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MySQL vs Qdrant

Compared 7% of the time

Elastic Search vs Qdrant

Compared 4% of the time

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Upstash vs Redis

Compared 5% of the time

Oracle Coherence vs Redis

Compared 5% of the time

Hazelcast Platform vs Redis

Compared 5% of the time

Azure Cache for Redis vs Redis

Compared 4% of the time

MongoDB Enterprise Advanced vs Redis

Compared 4% of the time

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Product Reports

Buyer's Guide

Qdrant

June 2026

Download Qdrant product report

Buyer's Guide

Redis

June 2026

Download Redis product report

Also Known As

No data available

Redis Enterprise

Overview

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.

Qdrant

Redis offers high-speed, in-memory storage, renowned for real-time performance. It supports quick data retrieval and is used commonly in applications like analytics and gaming.

Renowned for real-time performance, Redis delivers high-speed in-memory storage, making it a favorite for applications needing quick data retrieval. Its diverse data structures and caching capabilities support a broad array of use cases, including analytics and gaming. Redis ensures robust scalability with master-slave replication and clustering, while its publish/subscribe pattern renders it reliable for event-driven applications. The solution integrates smoothly with existing systems, minimizing performance tuning needs. Although documentation on scalability and security could be improved, Redis remains cost-effective and stable, commonly utilized in cloud environments. Enhancing integration with cloud services like AWS and Google Cloud and refining GUI may improve usability.

What are the key features of Redis?

High Speed: In-memory data storage for swift access.
Scalability: Master-slave replication and clustering for growth.
Data Structures: Supports diverse types for varied uses.
Persistence: RDB snapshots and AOF logs ensure durability.
Integration: Seamless integration reduces tuning efforts.

What should users look for in Redis reviews?

Performance: Real-time data retrieval boosts efficiency.
Cost-Effectiveness: Stable, budget-friendly implementation.
Versatility: Suitable for diverse environments and platforms.
Reliability: Ensures data persistence and high availability.

Redis finds application across industries for tasks like caching to improve application performance and speed, minimizing database load. It enables real-time processing for session storage, push notifications, and analytics. As a messaging platform, Redis handles high traffic and supports replication and clustering for cross-platform scalability.

Redis

Sample Customers

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

1. Twitter 2. GitHub 3. StackOverflow 4. Pinterest 5. Snapchat 6. Craigslist 7. Digg 8. Weibo 9. Airbnb 10. Uber 11. Slack 12. Trello 13. Shopify 14. Coursera 15. Medium 16. Twitch 17. Foursquare 18. Meetup 19. Kickstarter 20. Docker 21. Heroku 22. Bitbucket 23. Groupon 24. Flipboard 25. SoundCloud 26. BuzzFeed 27. Disqus 28. The New York Times 29. Walmart 30. Nike 31. Sony 32. Philips

Buyer's Guide

Qdrant vs. Redis

April 2026

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