Qdrant Reviews & Product Details

In our organization, we developed an RAG application and needed a way to store embeddings. I looked after many open-source tools like Pinecone and Superduperdb. Qdrant worked the best. The setup on our server was super easy, and their documentation is very elaborate. I also think the embedding search is more accurate than the other platforms I piloted with. We are still currently using Qdrant for our RAG application and are happy with it. Review collected by and hosted on G2.com.

Inability to perform rich operations from UI without writing code/query. For example, if I want to delete all collections or collections matching a name pattern, or even if I want to select multiple collections and delete, that is not possible through UI. Review collected by and hosted on G2.com.

Self-hosting Qdrant on a host is really simple and does not takes a lot of time to setup or troubleshoot issues. The documentation is also up to date. I prefer to install it using Docker to avoid installing dependencies. Review collected by and hosted on G2.com.

The initial learning curve is high but the documentation and resources makes up for it. Review collected by and hosted on G2.com.

What I like best about Qdrant is its efficiency in indexing and searching high-dimensional vectors. The ease of integration with AI-based applications and the ability to perform semantic search queries are major advantages. Additionally, the support for multiple programming languages makes Qdrant versatile and accessible for different development teams Review collected by and hosted on G2.com.

One of the few downsides of Qdrant is that the initial learning curve can be steep for those unfamiliar with vector-based databases. While the documentation is well-done, more practical examples or video tutorials would be helpful to ease the onboarding process for new users. Furthermore, some advanced features require manual configuration, which might not be straightforward for everyone. Review collected by and hosted on G2.com.

Qdrant is fast and easily scalable, and I can index and query millions of vectors, essential for my work on image search. This is true because it is an open-source application, thereby allowing me to modify and adapt it to other tools that I use. Review collected by and hosted on G2.com.

Qdrant does not have integrated visualizations. This makes it difficult to make conclusions and draw visualization of the search results. Review collected by and hosted on G2.com.

fully manage in all resource ,available on AWS , Google and azure plaform help with vector search technolgy Review collected by and hosted on G2.com.

non build in visualiztion ,significantly slower searching time in result. Review collected by and hosted on G2.com.

I can quickly scan through huge volumes of vectors – it is relevant for my AI work on image recognition. Since it is an open-source software, it can be used calmly and can be modified and integrated with my existing systems. Review collected by and hosted on G2.com.

Qdrant also has no incorporated visualization capabilities. Due to its basic functionalities I find it difficult to analyze and interpret the results as there are no additional software installed. Review collected by and hosted on G2.com.

In the pursuit of my AI research, Qdrant can expedite the process of searching high-dimensional vector data. The options and setting let me work on terabytes of data and perform similarity search in real time. Review collected by and hosted on G2.com.

Qdrant does not come with graphical utilities that can provide data visualization. This poses a problem when it comes to interpreting the retrieved results particularly for higher-orders of dimensions. Review collected by and hosted on G2.com.

A tool for creating vector collections and performing vector operations. It excels at vector distance searches, offers convenient auto-completion features, and includes a free tier for evaluation. Review collected by and hosted on G2.com.

Although the interface is quite simple, it still has limited capabilities. Review collected by and hosted on G2.com.

desparate data sources makes easier to consolidate and analyze data from various sources,scaling data,data quality and governance. Review collected by and hosted on G2.com.

Learning might be quite difficult for who are not familiar with advanved data analytics.

pricing plans are high. Review collected by and hosted on G2.com.

it is optimized for speed and scalability, capable of handling large datasets with high throughput. The engine uses state-of-the-art algorithms to ensure fast query responses. Review collected by and hosted on G2.com.

High performance comes with high resource usage, which might be a consideration for smaller deployments. Review collected by and hosted on G2.com.