I love how Zilliz excels at scalability and high-performance vector search, making it incredibly efficient for handling massive datasets in AI-driven tasks. In my experience, its hybrid retrieval capabilities—combining vector embeddings with knowledge graph integrations—stand out, especially for complex queries involving semantic understanding. It's easy to integrate with tools like LangChain and OpenAI embeddings, and the cloud-native features in Zilliz Cloud simplify management without sacrificing speed or accuracy. Review collected by and hosted on G2.com.

For self-hosted Milvus setups, the configuration might feel a bit involved compared to fully managed options, but Zilliz Cloud largely resolves that with its user-friendly UI and elastic scaling. Review collected by and hosted on G2.com.

1. Pay-as-you-go model: This is extremely important for individual developers like me — it greatly reduces financial pressure.

2. Affordable pricing: Even with the pay-as-you-go model, Zilliz offers a very competitive and reasonable price.

3. Easy data import: I can directly convert millions of vector records into large JSON files and upload them to the database easily — with zero additional cost during the upload process.

4. User-friendly experience: The official documentation is comprehensive, and the AI assistant efficiently helps solve any issues I encounter.

5. Excellent performance: Querying millions of vectors is lightning-fast — typically within 100 milliseconds. Review collected by and hosted on G2.com.

when uploading data, since the files are quite large, I need to manually upload multiple chunks. However, the upload management interface does not display the file names of each chunk on the main screen, which makes it difficult to tell which part of the data I’m currently importing. Review collected by and hosted on G2.com.

I truly love using Zilliz for building our video retrieval tool as it has greatly enhanced our ability to convert each frame of a video into vectors and store them effectively in Zilliz Cloud. This functionality allows for accurate and efficient searches for corresponding images or videos, whether making searches from text to images or vice versa. The support from Zilliz is impeccable, with a very active community and extremely reliable database systems, which gives us a great deal of confidence. The most impressive aspect is the retrieval speed; it is exceptionally fast, allowing us to search through millions of vectors in just 200 milliseconds, which is critical for our operations. Additionally, the ability of Zilliz to handle a large capacity of data further boosts its value, making our data management and retrieval processes smooth and efficient. Review collected by and hosted on G2.com.

I think the number of vector columns supported in a single collection is a bit low, it seems to be 4 or 8. We would like to be able to search across more dimensions. Review collected by and hosted on G2.com.

I am truly impressed by Zilliz's ability to handle a vast amount of data efficiently. Its capacity to store hundreds of millions of vector data points is remarkable. I find the vector retrieval process to be incredibly fast, characterized by its low latency, which is vital for my image similarity retrieval and content moderation needs. The platform's support for high-concurrency requests is another feature I value, as it ensures smooth operation even when handling multiple requests simultaneously. Additionally, the fact that Zilliz supports more than ten vector index types and offers rich functionality is a considerable advantage, simplifying operation and maintenance for my team. This richness in features also makes using Zilliz cost-effective. The initial setup was straightforward, simple, and clear, making it easier for us to integrate it with general-purpose embedding models. These aspects collectively make Zilliz an invaluable tool for our data storage and retrieval endeavors. Review collected by and hosted on G2.com.

There is a need for more comprehensive learning materials for Zilliz. Review collected by and hosted on G2.com.

Zilliz is the commercial version of Milvus, and it fits different business needs really well. First, it’s super fast when it comes to queries—super impressive. Then, for features, it supports both vector indexing and keyword indexing, so you’ve got way more flexible options there. And when picking the right type, it has capacity-focused, performance-focused, and tiered storage models. You can easily match what you need, whether that’s "fast response times" or "keeping costs down." Overall, it’s really practical and easy to use. Review collected by and hosted on G2.com.

Currently, it does not support slow query-related features.

Audit logs only support the Coordinated Universal Time Zero (UTC+0) time zone and cannot be adapted to other local time zones. Review collected by and hosted on G2.com.

I really appreciate how Zilliz supports hybrid retrieval, combining both vector and keyword searches. This feature is incredibly beneficial as it provides me with more accurate, context-aware results and ensures that I do not miss important exact matches. It’s very convenient to use, making my workflow more efficient. Additionally, the initial setup was a breeze thanks to Docker Compose and the clear documentation which guided me quickly through getting started. Review collected by and hosted on G2.com.

I find that sometimes the documentation could be more detailed, especially for advanced configurations and performance tuning. They could include more real-world configuration examples, detailed parameter explanations, and best practices for optimizing performance with large-scale hybrid retrieval workloads. Review collected by and hosted on G2.com.

As the cloud-native vector database platform, Zilliz has a large and active community, offers various solutions ranging from lightweight personal projects to million-concurrent production environments, and provides comprehensive open-source documentation where you can quickly look up details about development, deployment, and precautions. Review collected by and hosted on G2.com.

Due to the large community, there are many types and complex demands, which inevitably affect the development roadmap pace. Hope the team keeps up the good work. Review collected by and hosted on G2.com.

This product is quick, affordable, straightforward, and gets the job done. It's user-friendly and can easily scale to meet growing needs. Review collected by and hosted on G2.com.

Modifying collection schemas involves a migration process, which can be quite complex and often takes a significant amount of time to manage. Review collected by and hosted on G2.com.

The advantage of zillizCloud lies in its ease of use. You can easily get started by signing up for an account on the page and using the available SDK, making it suitable for beginners. ZillizCloud also offers excellent performance; compared to other databases I have used, its performance is currently the best. Review collected by and hosted on G2.com.

The only thing that might be less satisfying for me is the price, but they offer a suitable free quota. Not bad. Review collected by and hosted on G2.com.

It’s very easy to use and delivers powerful performance. Review collected by and hosted on G2.com.

The only issue is that the standalone deployment has a few too many dependencies. Review collected by and hosted on G2.com.