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Celonis vs Qdrant comparison

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Comparison Buyer's Guide

Executive Summary

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
7.0
Celonis drives substantial ROI through cost savings, efficiency, process improvements, and business transformation, with multimillion-dollar financial impacts.
Sentiment score
5.1
Qdrant offers financial benefits by reducing costs, improving efficiency, and boosting productivity through enhanced response times and HNSW searching.
In the first couple of years, I would not expect a return on investment because the initial setup will take more than a year if the process requires significant customization.
Senior Business Intelligence Analyst at a manufacturing company with 10,001+ employees
Automated exception handling cut manual process touchpoints by approximately 30 to 40%, saving approximately 15,000 to 20,000 operational labor hours annually.
PARTNER & MANAGING DIRECTOR at a financial services firm with 5,001-10,000 employees
In my opinion, there's a positive return on investment.
Head of Commercial Excellence at Sartorius AG
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
This lowers our LLM input token consumption by roughly 30 to 40 percent, translating directly into lower monthly OpenAI API bills.
MLOps Engineer at a tech services company with 501-1,000 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
 

Customer Service

Sentiment score
5.8
Celonis offers responsive support through various channels, though some users face delays and varying help based on contract size.
Sentiment score
4.4
Qdrant's customer service is lauded for its excellent support, active community, and comprehensive documentation, reducing direct support needs.
It took more than two weeks to receive a response.
Senior Business Intelligence Analyst at a manufacturing company with 10,001+ employees
Celonis customer support is really good; they investigate concerns thoroughly and provide solutions or troubleshooting steps, which I find helpful.
Process Mining Consultant at a tech vendor with 10,001+ employees
Other times I do not get much clarity on the support from the team.
Data Engineer at a pharma/biotech company 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
Qdrant's customer support is responsive and developer-focused.
MLOps Engineer at a tech services company with 501-1,000 employees
 

Scalability Issues

Sentiment score
7.1
Celonis is highly scalable, with strong integration capabilities, preferred over Tableau and Power BI for process mining.
Sentiment score
5.2
Qdrant excels in scalability, handling large data sets with efficient sharding, supporting rapid expansion and improved performance in Docker.
I recall that when we started using Celonis, we had a space of five terabytes and around one thousand users, and Celonis managed all of that easily.
Senior Business Intelligence Analyst at a manufacturing company with 10,001+ employees
I recommend focusing on recent data or perhaps five years of historical data along with live data for better visibility and stability in the process.
Process Mining Consultant at a tech vendor with 10,001+ employees
Consumption-based pricing models would be helpful because scaling can get costly quickly.
PARTNER & MANAGING DIRECTOR at a financial services firm with 5,001-10,000 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 is highly scalable, supporting both vertical and horizontal scaling across massive vector data sets.
MLOps Engineer at a tech services company with 501-1,000 employees
 

Stability Issues

Sentiment score
7.9
Celonis is highly stable, with minor connectivity issues resolved by upgrades, offering reliable and secure performance for users.
Sentiment score
7.8
Qdrant is reliable and accurate with high recall, precise vector matching, but requires regular updates and suffers inactive cloud termination.
It's super stable.
Head of Commercial Excellence at Sartorius AG
Celonis is stable.
Management Data Engineer & Governance Senior Analyst at a tech vendor with 10,001+ employees
Built in Rust, it delivers sub-15 millisecond response times and rock-solid update and write-ahead logging to guarantee that newly indexed data is immediately searchable without dropping queries or producing inconsistent context for LLMs.
MLOps Engineer at a tech services company with 501-1,000 employees
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
 

Room For Improvement

Celonis' high cost, complex setup, and integration challenges deter users, who seek improvements in usability, support, and documentation.
Qdrant users seek improved clustering, schema updates, multi-query fusion, intuitive UI, integration, and enhancements in native tools and features.
Ultimately, I need niche expertise, combining strong SAP knowledge with Celonis competency.
Head of Commercial Excellence at Sartorius AG
It is essential for the Celonis solution to have their services and solution models integrated with GenAI.
Senior Development Manager at Lutech
The most important area for improvement is the automation part.
Data Engineer at Baker Hughes
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

Celonis pricing is high, especially for scaling enterprises, with costs rising with users and data, but free versions exist.
Qdrant offers cost-effective, scalable solutions through open-source access and predictable pricing, suitable for enterprise scaling needs.
I think it's relatively expensive, but it's also good.
Head of Commercial Excellence at Sartorius AG
Based on client feedback, I have heard that the pricing for Celonis is considered high.
Senior Application Developer at Fujitsu
creating a data model for one process will differ in cost if you add more data models for additional processes.
Process Mining Consultant at a tech vendor with 10,001+ employees
The core product is open source under Apache 2.0, so initial experimentation and local integration testing cost nothing.
MLOps Engineer at a tech services company with 501-1,000 employees
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
 

Valuable Features

Celonis offers user-friendly process mining, integration, real-time analytics, and automation tools for optimizing efficiency and identifying savings opportunities.
Qdrant provides efficient, cost-effective search and deployment with advanced features, enhanced performance, and seamless cloud integration for AI projects.
Celonis is also beneficial for its built-in apps that streamline tasks from legacy applications, facilitating daily operations and improving efficiency.
Senior Application Developer at Fujitsu
The standout feature of Celonis is definitely the Process Intelligence Graph, which creates a living digital twin across multiple systems and provides the operational context needed for effective AI and automation.
PARTNER & MANAGING DIRECTOR at a financial services firm with 5,001-10,000 employees
It provides a visualization of the process itself, giving a very good synthesis of performance and helping me find improvements.
Head of Commercial Excellence at Sartorius AG
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
Qdrant supports high-dimension vectors and cosine similarity, which any vector database should have, and it is pretty fast.
CTO at Honeycomb AI
 

Categories and Ranking

Celonis
Ranking in AI Data Analysis
10th
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
60
Ranking in other categories
Process Mining (2nd)
Qdrant
Ranking in AI Data Analysis
6th
Average Rating
9.0
Reviews Sentiment
5.4
Number of Reviews
11
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 Celonis is 0.4%. 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
ProductMindshare (%)
Qdrant0.4%
Celonis0.4%
Other99.2%
AI Data Analysis
 

Featured Reviews

Prateek Rao - PeerSpot reviewer
PARTNER & MANAGING DIRECTOR at a financial services firm with 5,001-10,000 employees
Process intelligence has transformed procurement and order cycles and delivers measurable savings
Celonis can improve in several areas. The initial data modeling and continuous real-time ingestion, especially from non-standard legacy systems, can still be complex and quite resource-intensive, requiring a steep PQL learning curve for non-technical users. Simplifying the interface for business stakeholders would significantly accelerate the process. I think introducing a natural language to query interface would allow business users to query data without writing long PQL. Streamlining guided onboarding flows and offering modular plug-and-play dashboard templates tailored to specific roles would shorten ramp-up time for daily users. I think more transparent and predictable consumption-based pricing models would be helpful as data volume scaling can get costly quickly. I would also love to see native, real-time streaming connectors for unstructured data such as emails and support tickets. The learning curve for new users of Celonis is one of the pain points I raised earlier, and I find it to be quite steep.
Pawel Cislo - PeerSpot reviewer
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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Top Industries

By visitors reading reviews
Manufacturing Company
17%
Outsourcing Company
8%
Financial Services Firm
8%
Computer Software Company
8%
Comms Service Provider
12%
Manufacturing Company
12%
Financial Services Firm
9%
Computer Software Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business9
Midsize Enterprise6
Large Enterprise47
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise2
 

Questions from the Community

Which is better - Signavio Process Manager or Celonis?
SAP Signavio Process Manager is a very robust industrial-grade business process modeling tool. It is easy to use and does not require too much technological involvement. This solution has a collabo...
What is your experience regarding pricing and costs for Celonis?
I am not heavily involved in that particular aspect, but I have heard that Celonis is somewhat expensive.
What needs improvement with Celonis?
Celonis can improve in several areas. The initial data modeling and continuous real-time ingestion, especially from non-standard legacy systems, can still be complex and quite resource-intensive, r...
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...
 

Comparisons

 

Overview

 

Sample Customers

Anheuser-Busch InBev, AXA, Bayer, Cisco, Deloitte, Deutsche Telekom, Hitachi, Kellogg's, Lufthansa, and Whirlpool
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 Celonis vs. Qdrant and other solutions. Updated: September 2026.
915,341 professionals have used our research since 2012.