

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.
It is not primarily about cost optimization, but more about protecting our organization against ransomware attacks to avoid being brought to its knees.
We can see approximately 10% in savings, which could be in terms of time saving or money saving.
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.
This is a challenge for me, especially since I work in APAC, and whenever we engage with Veritas technical support, I must wait for someone in the United States to be available to help with our issue.
The IVR system should be reduced so that customers can reach support directly, as when someone calls, it is typically for a critical technical issue and the call should connect directly to a representative.
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.
Veritas Alta Data Protection is not expensive, which makes it scalable.
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.
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.
I want a very simple GUI which even an L1 engineer or L1 cloud engineer can understand and use with minimum supervision.
Veritas Alta Data Protection can be deployed on multiple cloud providers, including Azure and GCP.
The solution could benefit from some artificial intelligence features where we can restore files or get assistance from the AI side.
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.
Since we have been using Veritas Alta Data Protection for the last four years, the price is very friendly.
Regarding the pricing aspect, we received a pretty good discount when we started onboarding all of our backups to Veritas Alta Data Protection.
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.
The best features of Qdrant are GPU support, which enables very fast processing, and a very light footprint as it uses fewer resources.
We tested the effectiveness of Veritas Alta Data Protection's granular restoration feature during POC because we had a requirement to test various scenarios like restoring the bucket in a particular region, restoring the bucket in a different region, restoring EC2 instances, restoring containers, and databases.
The unique selling proposition includes automated policy-driven operations.
The best feature Veritas Alta Data Protection offers is integration with existing hyperscalers or virtual platforms as well as integration with current computing platforms, where we can see this working well with our existing scenarios.
| Product | Mindshare (%) |
|---|---|
| Qdrant | 0.4% |
| Veritas Alta Data Protection | 0.5% |
| Other | 99.1% |


| Company Size | Count |
|---|---|
| Small Business | 8 |
| Company Size | Count |
|---|---|
| Small Business | 3 |
| Midsize Enterprise | 1 |
| Large Enterprise | 5 |
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.
Veritas Alta Data Protection offers comprehensive data backup and recovery solutions tailored for enterprises, ensuring data safety and compliance.
Designed for seamless integration into complex IT environments, Veritas Alta Data Protection leverages advanced technology to provide reliable data protection, scalability, and ease of management. It caters to diverse sectors, supporting cloud-native and hybrid architectures while ensuring streamlined disaster recovery. Users find it valuable in optimizing backup processes, securing sensitive information, and maintaining high data integrity.
What are the key features of Veritas Alta Data Protection?In industries like finance and healthcare, Veritas Alta Data Protection is implemented to address critical data protection needs. It supports the secure handling of sensitive customer information and adheres to stringent compliance mandates, ensuring continuous protection and availability of essential data resources.
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