

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.
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.
The time saved is substantial, with nearly three weeks or more for projects deployed with Qdrant Cloud in no-code platforms.
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.
In my organization, we moved from OBI to Qlik Sense due to limitations with OBI, resulting in very high ROI.
It's open source, so we house it on our server.
The documentation provided by Qdrant covers most queries effectively.
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.
While tech support is comprehensive, the stability of Qlik Sense means I generally do not need it.
Technical support requires improvement.
In Turkey, the consultant firms are very professional, and they support you.
In the recruiting agency project, the reliance on the vector database has expanded from storing hundreds of resumes to thousands.
When Qdrant is deployed in Docker, it scales really fast, and you can assign multiple CPUs to enhance performance.
Qdrant handles growing workloads and data volumes well for me, which was a significant reason for my shift from other popular alternatives to Qdrant.
It performs well in terms of performance and load compared to others.
Qlik Sense helps analyze data and can handle larger amounts of data compared to other BI tools.
It is easily scalable with Microsoft, with other services Azure and other tools they provide.
You need to patch Qdrant as soon as patches are released.
It is easy to use whether on LangChain or on its own.
Qdrant is stable, except for the limitation concerning the termination of inactive clouds after a week.
The stability is very good.
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.
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.
Incorporating embedding features directly in Qdrant Cloud would eliminate the need to depend on external solutions.
Power BI has better visualizations and interactions with updates in 2023 that provide ease of use.
Providing an API feature to access data from the dashboard or QEDs could be beneficial.
There should be more comprehensive documentation and explanatory videos available to help clients understand and calculate capacity-based pricing, making it easier to predict costs before implementing Qlik Sense Cloud.
Using Qdrant is free.
Regarding pricing, setup costs, and licensing, since I am using only the free tier of Qdrant Cloud, there are no setup costs involved.
Licensing posed no issues, as Qdrant is open-source software with no upfront fees.
It is just about how expensive it is to implement.
Compared to Power BI, it is definitely costly.
Among the BI tools and data analytics tools, Qlik is the most expensive.
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.
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.
Qdrant supports high-dimension vectors and cosine similarity, which any vector database should have, and it is pretty fast.
From an end-user perspective, it's convenient and performance-oriented, providing something meaningful from all the organization's data.
The true power is in the ability to connect with any database, get the data, and work with the data.
Real-time data analysis can be performed, and collaboration with other team members is seamless.
| Product | Mindshare (%) |
|---|---|
| Qdrant | 0.4% |
| Qlik Sense | 0.4% |
| Other | 99.2% |


| Company Size | Count |
|---|---|
| Small Business | 10 |
| Midsize Enterprise | 1 |
| Company Size | Count |
|---|---|
| Small Business | 34 |
| Midsize Enterprise | 40 |
| Large Enterprise | 89 |
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.
Qlik Sense offers drag-and-drop dashboard creation, multi-data source integration, and self-service analytics. Users benefit from associative data modeling and real-time insights. The platform enhances quick deployment across any device with its flexibility and ease of use.
Qlik Sense provides rapid dashboard creation and seamless multi-data source integration, supporting real-time analytics and high-speed ETL capabilities. Users enjoy advanced visualizations and natural language processing within an intuitive interface. The solution's in-memory engine ensures fast data processing while offering flexibility and quick deployment on all devices. Its open API facilitates extensive customization and integration with chatbots and third-party extensions.
What are the key features of Qlik Sense?In industries such as finance and sales, Qlik Sense enables interactive data analyses and dashboard creation across departments. It supports business intelligence for financial reporting, sales analysis, and decision-making. By automating reporting and combining data from multiple sources, it facilitates users in generating insights and enhancing data accessibility for informed business decisions.
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