DataStax Enterprise vs Milvus comparison

IBM and The Milvus Project are both solutions in the Vector Databases category. IBM is ranked #15 with an average rating of 8.6, while The Milvus Project is ranked #12 with an average rating of 8.0. IBM holds a 1.8% mindshare in VD, compared to The Milvus Project’s 6.9% mindshare. Additionally, 100% of IBM users are willing to recommend the solution, compared to 100% of The Milvus Project users who would recommend it.

DataStax Enterprise

Read 5 DataStax Enterprise reviews

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641 Comparison Views

100% willing to recommend

Milvus

Read 5 Milvus reviews

3,898 Views
3,313 Comparison Views

100% willing to recommend

DataStax Enterprise

Milvus

Comparison Buyer's Guide

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Executive SummaryUpdated on Feb 8, 2026

DataStax Enterprise and Milvus are competing products in data management and analytics. DataStax Enterprise seems to have the upper hand with its comprehensive support and scalability.

Features: DataStax Enterprise offers advanced data replication, security, and analytics capabilities suitable for large-scale, real-time applications. It ensures robust real-time system solutions and efficient data management across different environments. Milvus provides efficient handling of vector data crucial for AI models, managing high-dimensional data effectively, making it ideal for AI-driven applications with a focus on specialized vector database solutions.

Ease of Deployment and Customer Service: DataStax Enterprise offers a well-documented enterprise-grade deployment model with extensive customer support, ensuring smooth setup and operation. Milvus adopts an open-source approach with various integrations and community-driven support, appealing to users seeking flexibility.

Pricing and ROI: DataStax Enterprise typically involves higher setup costs due to its extensive features and support, potentially leading to strong ROI for enterprise deployments. Milvus offers a more economical option with lower upfront costs, making it appealing to startups and AI-focused companies looking for cost-effective solutions.

To learn more, read our detailed DataStax Enterprise vs. Milvus Report (Updated: April 2026).

Buyer's Guide

DataStax Enterprise vs. Milvus

April 2026

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

DataStax Enterprise

Ranking in Vector Databases

15th

Average Rating

8.6

Reviews Sentiment

7.4

Number of Reviews

Ranking in other categories

NoSQL Databases (10th)

Milvus

Ranking in Vector Databases

12th

Average Rating

7.4

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

Open Source Databases (10th)

Mindshare comparison

As of May 2026, in the Vector Databases category, the mindshare of DataStax Enterprise is 1.8%, up from 0.5% compared to the previous year. The mindshare of Milvus is 6.9%, down from 8.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Vector Databases Mindshare Distribution
Product	Mindshare (%)
Milvus	6.9%
DataStax Enterprise	1.8%
Other	91.3%

Vector Databases

Featured Reviews

Suzanne Kimono

Senior Software Engineer at Deloitte

Continuous data access has ensured high uptime and has supported real-time transactional processing

The best features DataStax Enterprise offers include scaling, speed of data access, and ease of use for those familiar with traditional SQL. The scaling and speed of data access have benefited my team because the scaling and the speeding of data provide linear scale as well as multi-data centers' real-time replication of data such that we can maintain uptime even with the loss of multiple data centers. It enables us to maintain our uptime, which is very crucial for our clients. DataStax Enterprise has positively impacted my organization by providing the ability to have our services up and running even with a total outage at one of our data centers. There is no need to maintain windows since we can turn off data centers while doing maintenance and then put them back in the rotation and move on. I can share specific outcomes or metrics that show this positive impact, such as improvements in performance of about 60% and a reduction in downtime of about 40 to 45%, which is very great.

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reviewer2395743

Data Scientist at a tech services company with 1,001-5,000 employees

Helps convert text and other data into a vector space but could provide detailed insights

Milvus is an open-source vector database designed for efficiently handling large-scale, high-dimensional data. It supports various types of data sources and can be deployed on your own premises, which is crucial for maintaining data security. Milvus offers multiple methods for calculating similarities or distances between vectors, such as L2 norm and cosine similarity. These methods help in comparing different vectors based on specific use cases. For instance, in our use case, we find that the L2 distance works best, but you can experiment with different methods to find the most suitable one for your needs. Milvus also includes its own user interface, known as the Milvus Dashboard, which allows you to visualize and manage your data, including embeddings and metadata. You can filter your data based on various criteria, including metadata and file names, which provides flexibility in data management.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"DataStax Enterprise positively impacted my organization by allowing us to contribute to our main feature development in the product and not worry much about these different services."

"DataStax Enterprise has positively impacted my organization as we are now an e-commerce website that has never faced downtime, which helps our business to boom and significantly enhances our customer experience."

"I can share specific outcomes or metrics that show this positive impact, such as improvements in performance of about 60% and a reduction in downtime of about 40 to 45%, which is very great."

"I can share specific outcomes resulting from using DataStax Enterprise as we have been seeing an uptick in user adoption, since the introduction of this, our users have jumped from around 20,000 to 50,000."

"Some of the positive outcomes I see are that system stability improved a lot, there is no single point of failure, so downtime is reduced significantly, and the system stays up even when we face issues in a node."

"Milvus has good accuracy and performance."

"The best feature of Milvus was finding the closest chunk from a huge amount of data."

"Milvus offers multiple methods for calculating similarities or distances between vectors, such as L2 norm and cosine similarity. These methods help in comparing different vectors based on specific use cases. For instance, in our use case, we find that the L2 distance works best, but you can experiment with different methods to find the most suitable one for your needs."

"The solution is well containerized, and since containerization is quick and easy for me, I can scale it up quickly."

"I like the accuracy and usability."

Cons

"I believe that DataStax Enterprise could be improved by working more on making the OpsCenter user interface more user-friendly, particularly regarding the fonts and overall UI."

"My experience with pricing, setup cost, and licensing is that I feel the cost is a bit expensive compared to the open-source implementation of Cassandra, and the initial cluster setup is complex."

"There is still room for improvement and DataStax Enterprise can definitely improve their UI."

"If not keeping current with updates, updating from an older major version to a newer major version can be a bit complicated and time-consuming, but DataStax Enterprise support will help us with this."

"Milvus' documentation is not very user-friendly and doesn't help me get started quickly."

"Milvus could make it simpler. Simplifying the requirements and making it more accessible. It could be more user-friendly."

"I've heard that when we store too much data in Milvus, it becomes slow and does not work properly."

"Milvus has higher resource consumption, which introduces complexity in implementation."

Pricing and Cost Advice

Information not available

"Milvus is an open-source solution."

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Top Industries

By visitors reading reviews

Financial Services Firm

14%

Retailer

10%

Manufacturing Company

10%

Media Company

10%

Computer Software Company

14%

Financial Services Firm

Manufacturing Company

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	2
Large Enterprise	5

No data available

Questions from the Community

What is your experience regarding pricing and costs for DataStax Enterprise?

My experience with pricing, setup cost, and licensing indicates that the cost is a bit affordable, especially for my organization. However, for smaller organizations working under a tight budget, i...

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What needs improvement with DataStax Enterprise?

DataStax Enterprise can provide other solutions that are well-suited for other use cases such as an auditing system or writing systems. Additionally, many other details can be provided for monitori...

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What is your primary use case for DataStax Enterprise?

My main use case for DataStax Enterprise is handling the high-volume transactional data in a distributed system. I work on an application where we need to store and process a large amount of real-t...

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What do you like most about Milvus?

I like the accuracy and usability.

See all answers

What needs improvement with Milvus?

Milvus could be improved how it could automatically generate insights from the data it holds. Milvus maintains embedding information and knows the relationships between data points. It would be use...

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What is your primary use case for Milvus?

Milvus is primarily used in RAG, which involves retrieving relevant documents or data to augment the generation of new content. Milvus helps convert text and other data into a vector space, and the...

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Comparisons

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Compared 12% of the time

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Compared 11% of the time

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Compared 6% of the time

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Compared 9% of the time

Elastic Search vs Milvus

Compared 8% of the time

LanceDB vs Milvus

Compared 8% of the time

MongoDB Enterprise Advanced vs Milvus

Compared 8% of the time

ClickHouse vs Milvus

Compared 6% of the time

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Product Reports

Buyer's Guide

DataStax Enterprise

May 2026

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Buyer's Guide

Open Source Databases

May 2026

Download Milvus product report

Overview

DataStax Enterprise offers a high-performance, scalable database solution designed for modern data requirements, supporting a wide array of use cases that demand real-time analytics and robust security.

Focusing on delivering powerful distributed databases, DataStax Enterprise integrates the open-source foundation of Apache Cassandra, delivering enhanced features for enterprises. It supports mission-critical applications at scale, providing real-time query capabilities and fault tolerance. Designed with high availability and operational efficiency, it supports complex data models and simplifies management with advanced tools for monitoring and repair.

What are the standout features of DataStax Enterprise?

Advanced Security: Provides comprehensive data protection with encryption and identity management.
Graph Database Support: Allows complex data relationships to be easily modeled and queried.
Search Integration: Facilitates full-text search capabilities combined with Cassandra's strengths.
Analytics: Offers integrated analytics with Apache Spark for real-time data processing.
Multi-Cloud Support: Ensures easy deployment across different cloud environments without vendor lock-in.

What benefits should reviews highlight?

Scalability: Seamlessly expands to accommodate growing data volumes and user demands.
Performance: Maintains high-speed data processing even at massive scales.
Resilience: Provides high availability to ensure business continuity.
Cost Efficiency: Enables optimization of infrastructure investments with flexible deployments.

In industries such as finance, telecommunications, and retail, DataStax Enterprise is implemented to handle immense data workloads, often leveraging its capabilities for fraud detection, personalized customer experiences, and real-time decision-making. Its deployment in these sectors highlights its adaptability and performance in demanding environments.

IBM

Milvus is a powerful tool for efficiently storing and retrieving large-scale vectors or embeddings. It is widely used in applications such as similarity search, recommendation systems, image and video retrieval, and natural language processing.

With its fast and accurate search capabilities, scalability, and support for multiple programming languages, Milvus is suitable for a wide range of industries and use cases.

Users appreciate its efficient search capabilities, ability to handle large-scale data, support for various data types, and user-friendly interface.

Milvus enables easy retrieval of information from vast datasets, regardless of the data format, and is praised for its high performance and scalability. The intuitive and easy-to-use interface is also highlighted as a valuable aspect of the platform.

The Milvus Project

Sample Customers

ING, Netflix, UBS, eBay, Constant Contact, Aeris, Arise, ClearCapital, Dyn, Engine, Noble Group, Pantheon, Target

1. Alibaba Group 2. Tencent 3. Baidu 4. JD.com 5. Meituan 6. Xiaomi 7. Didi Chuxing 8. ByteDance 9. Huawei 10. ZTE 11. Lenovo 12. Haier 13. China Mobile 14. China Telecom 15. China Unicom 16. Ping An Insurance 17. China Life Insurance 18. Industrial and Commercial Bank of China 19. Bank of China 20. Agricultural Bank of China 21. China Construction Bank 22. PetroChina 23. Sinopec 24. China National Offshore Oil Corporation 25. China Southern Airlines 26. Air China 27. China Eastern Airlines 28. China Railway Group 29. China Railway Construction Corporation 30. China Communications Construction Company 31. China Merchants Group 32. China Evergrande Group

Buyer's Guide

DataStax Enterprise vs. Milvus

April 2026

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