

Find out in this report how the two Open Source Databases solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
What was projected for a three-year hardware lifespan extended to five years, yielding a return on investment of more than two times from migrating from MySQL to Percona Server.
I have seen a return on investment from using Percona Server, especially in terms of time, as time to resolve issues and time to get notified mean that time is a lot of money.
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.
Percona Server's customer support is excellent with very responsive and friendly service.
support was quite helpful in assisting us with archivers, replicators, and other commands.
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.
Percona Server's scalability is very strong, as it features thread pooling for over 10,000 connections.
We find it is easy to scale out and scale in using Percona Operator, Percona XtraDB toolkits, and PXC XtraDB Cluster.
Percona Server's scalability meets our needs well, as we use it in Docker and scale the way we want with multiple MongoDB servers rather than one huge server.
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.
Percona Server is perfectly stable and reliable.
Percona Server is very stable in my experience.
Percona Server is stable based on my experience.
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.
It would be helpful to clarify the metrics related to disk I/O latency so we could understand where our bottlenecks are.
I believe it would be great to have tools to deploy Percona Server in Docker so that we can split a huge database server into many small servers, which are easier to maintain and delegate to junior administrators.
The introduction of materialized views in Percona Server would be a significant help, as this feature has been requested for a long time.
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.
What I appreciated was that they packaged support with the licenses, ensuring that we ended up with a working database.
we received the enterprise features for free
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.
Percona Kubernetes for MongoDB is a unique offering since no other companies provide a proper Kubernetes operator that supports deployment, maintenance, and backup.
Percona Server has positively impacted my organization by allowing us to save a ton of money by not having to use RDS or Aurora in Amazon.
Whenever there is an issue, Percona Server notifies us, and we resolve the issue immediately.
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.
| Product | Mindshare (%) |
|---|---|
| Qdrant | 4.4% |
| Percona Server | 2.4% |
| Other | 93.2% |


| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 3 |
| Large Enterprise | 3 |
| Company Size | Count |
|---|---|
| Small Business | 10 |
Percona Server is a MySQL alternative offering improved performance and scalability for databases used in demanding environments. It is tailored for companies requiring reliable data management, ensuring efficiency and flexibility in operations.
Percona Server enhances MySQL with numerous features that boost database performance, making it suitable for large-scale deployments. Known for its ability to handle heavy workloads, users count on Percona Server to maintain operational consistency even under significant demand. Its security and compatibility with MySQL are additional benefits, providing a seamless transition for existing MySQL users. Organizations focused on cost-efficiency and high performance often consider Percona Server as a strong, open-source solution.
What are Percona Server's features?In industries such as e-commerce, telecommunication, and finance, Percona Server is implemented to maintain high transaction volumes and ensure robust data security. Its utility in managing complex database demands makes it a preferred choice in sectors where data integrity and performance are crucial.
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.
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