Milvus vs. Elastic

If I were to choose again, I would still choose Milvus at this point. The scalability, documentation quality, and continuous innovation make it the right foundation for our plagiarism detection platform."

Teis Petersen

Engineering Team Lead, UNIwise

Milvus has done an extraordinary job in revolutionizing Likee's video deduplication system, which significantly fueled the growth of BIGO's short-video business."

Xinyang Guo

Software Engineer at BIGO

Milvus has dramatically facilitated the MMU team in building various business systems and effectively supports our rapid business growth. Thanks to the Milvus team for developing such a fantastic vector database with stable vector search capabilities and rich functionalities."

The MMU team

Shopee

Our search system has been much more intelligent, stable, and reliable using Milvus. "

Rahul Yadav

Software Engineer at Tokopedia

We plan to expand the use of Milvus in different fields like content moderation and restriction and customized video services. BIGO and Milvus working together will benefit both businesses and I look forward to Milvus and its community to keep growing and prosper."

Xinyang Guo

Software Engineer at BIGO

I was benchmarking different vector databases, and Milvus was at the top among all the popular options on the market."

Saumil Patel

the Senior Data Scientist from Ivy.ai

We've gained so much from the Milvus community that we decided to contribute features like "hot reload," which have also benefited our internal operations."

Dennis Zhao

AI Infrastructure Lead at SmartNews

Milvus delivers unparalleled performance and flexibility, integrating seamlessly with leading vector index libraries like Faiss. Its intuitive API and robust solutions for high availability make it an indispensable tool in our APK security efforts."

Wei Huang

Senior Research Engineer

Milvus consistently outperformed Weaviate, emphasizing the indexing time for scenario S9, closely resembling the FARFETCH product catalog's dimensions."

PEDRO MOREIRA COSTA

Applied Scientist

When you're engineering a solution as complex as ours, you're not just ticking boxes—you're looking for that sweet spot where all your must-haves intersect. Think of it as an eight-circle Venn diagram; while many databases met one or two of our criteria, Milvus was the only one sitting right at the intersection of all eight. It checked every single box for us—something no other solution managed to do."

Jack Fischer

Co-founder & CTO at Credal AI

'wellSpent' is an intuitive mobile application designed to simplify and visualize spending habits. At its core, wellSpent displays a dynamic pie chart that offers a snapshot of expenditures. Users can access detailed transaction lists and explore predictive features like the travel planner, student debt planner, and other expense planners, all designed to optimize their financial journey. Built on Flutter and powered by Firebase, wellSpent stands as a testament to ensuring every penny is, indeed, well spent."

The wellSpent Team

at HackNC

Milvus has not only streamlined but also remarkably expedited the retrieval of millions of semantic vectors, showcasing a nearly tenfold improvement compared to our previous experience with other vector similarity search engines."

Tingting Wang

NLP Algorithm Engineer at Sohu

Milvus searches tens of millions of vectors in milliseconds, providing optimal performance while keeping development costs low and resource consumption minimal. "

Yu Fang

AI scientist at Mozat

Creating a user-centric interface that's both intuitive and efficient tops our list. We're also immensely proud of the predictive features – like creating comprehensive tools that will tell you how you can save money even after a transaction, along with other tools like customer trip planner already built using your spending transactions and trends. Using vector databases was our first time, and we are very proud of our outcome."

The wellSpent Team

at HackNC

When it comes to vector databases, Milvus has impressed us with its performance and scalability, meeting our stringent criteria for handling our AI use case backlog."

Toby Yu

Team Lead of AI, ML, and Platform Solutions

Milvus-powered vector search has been running steadily in our recommendation systems, providing high performance and allowing us more flexibility in selecting models and algorithms."

VIPSHOP Search Service Team

VIPSHOP

During batch ingestion tests, Milvus demonstrated that it could complete an entire collection dump into the database at speeds 5-10 times faster than competitors."

Toby Yu

Team Lead of AI, ML, and Platform Solutions

Zilliz Cloud stood out for us with its comprehensive range of index types, automatically optimizing for the perfect balance between recall and performance. Its robust security and private networking features, combined with the advantage of a fully-managed database, have significantly lightened our operational load, enabling us to concentrate on driving innovation rather than managing backend complexities. "

Ben Kramer

Co-founder & CTO of Monterey AI

When we conducted our first test run (on Zilliz Cloud), the performance improvement was astonishing. Our search time went from eight seconds down to sub one second. We were nearly falling off our chairs with amazement at the speed."

Alex Alexander

Co-founder & CEO of Picdmo Inc.

You can think of LlamaIndex as a black box around your data and LLM."

Jerry Liu

Co-founder and CEO of LlamaIndex

Zilliz Cloud perfectly aligns with MindStudio's vision. Its high-performance, secure platform and multi-tenancy simplifies data management and unlocks unprecedented productivity and innovation for our users’ AI applications. "

Sean Thielen

CTO @ MindStudio

As our business has expanded, the demands on our vector database have increased. We need a solution that minimizes operational costs, offers elastic scaling capabilities to manage vast amounts of vector data and unexpected traffic surges, provides faster vector search speeds, and ensures a high service level agreement (SLA)."

Chenhui Li

Tech Lead at Shulex

I appreciated using the open standard evaluation benchmarks for machine learning in general; this is also true for vector databases. The ones that Zilliz often publicizes have been beneficial, and the fact that they are open is significant. "

Sam Butler

Director of Machine Learning @ Dopple.AI

I can set up Milvus for scale in an hour, not overthinking it, and have a clear architecture path forward to grow my use case much larger without having to redo everything."

Zen Yui

Co-founder & CTO at Troop

Reliability, scalability, and performance are great. The fact that we can outsource all this kind of administration management and don't have to worry about servers breaking helps us put resources into product development and innovation, which truly differentiates our business. "

Michal Oglodek

CTO of Ivy.ai

Since transitioning from the open-source Milvus vector database to the fully managed Zilliz Cloud, we’ve experienced significant improvements in business performance. We’ve achieved lower operational costs, increased search speed, a more flexible system architecture, and a more stable user experience. Zilliz Cloud also provides expert support to resolve issues quickly and effectively. Overall, Zilliz Cloud has given us greater convenience and a competitive edge, and we are very pleased and optimistic about this change."

Shengyi Pan

CTO of Shulex

Even with numerous concurrent searches, we didn’t notice any slowdown in search speed with Milvus."

Mr. Zhang

BOSCH’s principal software engineer

We need an indexing technology that can handle complex search requirements and generative models, reduce training costs, improve update efficiency, and adapt flexibly to evolving data and query needs."

Mr. Zhang

BOSCH’s principal software engineer

When we identify a need for specific data, we can often find the required data in our database the same day using text or image search with Milvus. This greatly improves our data processing efficiency and has a positive effect on our business operations."

Mr. Zhang

BOSCH’s principal software engineer

I really like how Milvus' hybrid search allowed me to blend semantic and keyword search, which is crucial in a domain as technical and complex as EU policy."

Alessandro Saccoia

Co-Founder @ Veridien.ai

Milvus is renowned as one of the most advanced vector database platforms for AI applications. Rakuten Symphony engineers identified the Milvus Vector Database - an open source database which is horizontally scalable - as their platform of choice for LLM use and developing and maintaining AI applications."

Rakuten Symphony Engineering Team

Zilliz Cloud gave us the speed and scale we needed to power visual search at Leboncoin, meeting our sub-200ms latency target and making product discovery seamless for millions of users."

Yann Lemonnier

ML Engineer

Zilliz is a very integral part of our workflow. If we just swapped Zilliz Cloud with something else, the kind of loops that we get might not make sense, which means the end composition might not sound very nice or might not be very accurate to the text prompt you had given."

Sangarshanan Veera

Senior Software Engineer at Beatoven.ai

The competitive advantage for meeting transcription products in the future will come from personalization – providing tailored insights and recommendations based on each user's specific meeting data and usage patterns. This is why performant vector search is imperative."

Dai Tongjie

CTO

Zilliz Cloud enabled us to scale search while dramatically reducing our costs. Its hybrid search capabilities helped us achieve higher relevance for both text and image queries."

Celine Lightfoot

CTO of Beni

With Zilliz Cloud, we've achieved query latencies as low as 5-10ms across our million-vector database. This represents performance that's twice as fast as our previous solution, which directly translates to more responsive chatbots for our customers."

Nguyễn Ngọc Hải Đăng_ Nguyễn Nhật Khoa

AI Engineer at CX Genie

After integrating Zilliz Cloud vector database service, our system performance has significantly improved. During implementation, the Zilliz Cloud expert team provided excellent support and assistance, giving our EviMed platform a strong competitive advantage in the industry."

Dr. Zeyuan Wang

CEO of EviMed

Milvus has become the only technical choice for vector databases in our upcoming business expansion across the life sciences industry."

Xiaoming Zhang

VP of Technology at Biomap

Als sich Meituan zu KI verpflichtete, brauchten wir eine Retrieval-Grundlage, die von Grund auf für Vektoren gebaut wurde. Wir wählten das Open-Source-Milvus und machten daraus eine Plattform, auf der jedes Team aufbauen kann. Ein Jahr später enthält sie mehr als 10 Milliarden Vektoren und betreibt unsere am schnellsten wachsenden KI-Workloads – von RAG bis zum Agentengedächtnis."

The Meituan Database Team

By migrating to Zilliz Cloud, we've reduced our vector database infrastructure costs by approximately 70% compared to our self-hosted setup. This allows us to reinvest those savings into improving our core AI capabilities rather than managing database infrastructure."

Nguyễn Ngọc Hải Đăng_ Nguyễn Nhật Khoa

AI Engineer at CX Genie

Thanks to the well-designed Python SDK and REST API, we were able to integrate Zilliz Cloud with our LangChain-based architecture in a matter of days. The schema-based collections perfectly aligned with how we structure our data, making the transition nearly seamless."

Nguyễn Ngọc Hải Đăng_ Nguyễn Nhật Khoa

AI Engineer at CX Genie

When it comes to vector databases, Milvus has impressed us with its performance and scalability, meeting our stringent criteria for handling our AI use case backlog."

Team Lead

AI, ML, and Platform Solutions

During batch ingestion tests, Milvus demonstrated that it could complete an entire collection dump into the database at speeds 5–10 times faster than competitors."

Team Lead

AI, ML, and Platform Solutions

We've got millions of monthly active users and all of the underlying data when we're trying to go find related conversations, find updates to an action item, find referenced documents...Milvus serves as the central repository and powers our information retrieval among billions of records."

Rob Williams

Co-Founder and CTO at Read AI

Working with Zilliz Cloud has been transformative for our AI agent architecture. The hybrid search capability alone delivered a 40% accuracy improvement, and the scalability means we never worry about performance, even during the highest traffic periods. It's been essential to our continued growth."

Sasidhar Janaki

Senior Software Engineer at Rexera

As a client of a law firm, at some point clients will demand that their law firms use AI because it's going to make them a better attorney to have the curation done versus some of the practices now where they just don't have complete info."

Brianna Connelly

AI Team Lead at Filevine

We have achieved a true consciousness of data... bringing the data together in the way that an individual doing their job needs to see it."

Nathan Morris

Co-Founder of Filevine

We were facing latency issues and scaling challenges with our previous solutions. When traffic spiked with millions of customer requests, our self-hosted infrastructure couldn't keep up, and document retrieval was taking too long. "

Sasidhar Janaki

Senior Software Engineer at Rexera

Wir antworten in unter 20 Millisekunden über Hunderte Millionen Vektoren, und jedes KI-Produkt, das wir gebaut haben — Suche, Werbung, RAG — läuft auf derselben Milvus-Bereitstellung. Das ermöglicht es uns, weiterhin auszuliefern, ohne Infrastruktur hinzuzufügen."

Nam Doan Ngoc Giang

Lead Data Scientist, Cốc Cốc

Milvus scaled really well with batches ranging from 1,000 to millions of records. That really impressed me."

Todor Voynikov

Data Engineer at TrialHub

What we wanted was to push intelligence to the user before they even asked. Milvus is what made that viable."

Rob Williams

Co-Founder and CTO at Read AI

We have the full end-to-end data... law as a timeline. We have the incident, the start, everything that's happening, and the conclusion of the case. There's an enormous amount of power in having that all within the work system."

Brianna Connelly

AI Team Lead at Filevine

Kreative erstellen nicht ein einzelnes Bild und gehen dann. Sie bauen eine Figur, eine Welt, eine Geschichte auf, und alles, was sie je generiert haben, wird zum Material für die nächste Szene. Zilliz Cloud ermöglicht es uns, diese gesamte Bibliothek wie ein einziges kreatives Gedächtnis zu behandeln."

John Qiao

Co-founder & CTO, OpenArt

It has saved us cost by at least 25 to 30% on what we were earlier incurring on the vector database, with potential savings reaching up to 40-50% during peak traffic periods. "

Rachit Jindal

Senior AI Engineer at Verbaflo.ai

We were running a multilingual RAG system at scale, indexing all of Wikipedia into tens of millions of high-dimensional vectors. Latency targets were tight. We needed a system that could handle real-time retrieval over millions of knowledge vectors without breaking under load. Zilliz gave us that. It freed up engineering cycles and let us focus on improving reasoning on the model side, not managing infrastructure. That reliability mattered because we were operating at 3,500+ dimensions per vector, across a fast-growing corpus, with sub-300ms latency requirements in production. "

Dr. Pratyush Kumar

Co-Founder of Sarvam

It was the best thing to offer—performance-wise, cost-wise, and ease-of-use-wise."

George Kastrinakis

Director of Data Science and AI Services at Orfium

„Unsere alte Suche benötigte bei P99 25 Sekunden. Das war inakzeptabel. Zilliz Cloud hat sie auf unter eine Drittelsekunde gebracht und uns ermöglicht, den Retrieval-Code zu löschen, den wir bisher selbst gewartet hatten.""

Danny Xiong

Software Engineer, OpenArt

Choosing Zilliz Cloud was one of our best early decisions. It enabled us to build the product we envisioned rather than the product our infrastructure limitations would allow. In AI applications, that difference often determines success or failure."

Ethan Zheng

Co-Founder & CTO of Jobright.ai

KI verändert, wie Menschen Inhalte entdecken und genießen, und Kwai möchte diese Veränderung anführen. Milvus bietet uns die Leistung, Stabilität und Offenheit, die wir brauchen, und ist zu einem zentralen Bestandteil unserer KI-Infrastruktur geworden."

Di Wang

Senior Database R&D Engineer at Kuaishou

The sub-10 millisecond latency for queries is quite the benchmark in the industry for vector databases. Combined with the cost savings and reliability, Zilliz Cloud has become a strategic enabler for our broader vision of transforming conversational AI across industries."

Rachit Jindal

Senior AI Engineer at Verbaflo.ai

With Zilliz Cloud, we moved from operating at our limits to building with confidence. It gave us the scale, performance, and flexibility to protect music rights in real time—something we couldn’t achieve with traditional systems."

George Kastrinakis

Director of Data Science and AI Services at Orfium

Our strongest competitive moat isn't our AI models—it's our ability to deploy those models at scale with an exceptional user experience. Zilliz Cloud gave us that capability."

Ethan Zheng

Co-Founder & CTO of Jobright.ai

Milvus’s real advantage was how easy and friendly it made things to understand and execute."

Hanlian Lyu

a Product Owner and BI Expert at Volvo Cars

From a system stability perspective, it's really quite good. Over the year-plus that we've been using it—from version 2.4.3 to now 2.5.8—I honestly haven't encountered many issues. The system can just run there for months, with new data being written every day and users searching every day, without any problems. I don't need to worry about it."

Team Lead

Senior Infrastructure Engineer

Among Milvus's rich vector search capabilities, features such as support for multiple ANN index types, multi-vector support, and hybrid search have proven especially valuable in real-world service environments. As Milvus continues to evolve with new capabilities, NAVER expects even broader applications across its services."

NAVER Engineering Team

From a system stability perspective, it's really quite good. Over the year-plus that we've been using it—from version 2.4.3 to now 2.5.8—I honestly haven't encountered many issues. The system can just run there for months, with new data being written every day and users searching every day, without any problems. I don't need to worry about it."

Jianping Wang

NVIDIA engineer

Milvus transformed our ability to detect semantic plagiarism at scale. We can now process variable workloads ranging from 10 to 10,000+ documents daily while maintaining cost-effectiveness, which would have been impossible with traditional solutions."

Teis Petersen

Engineering Team Lead, UNIwise

We tested every mainstream vector database, and Milvus delivered the best overall performance."

Su Wei

CTO of Shining

Milvus has become the bridge that connects our multi-modal foundation models with real-world applications. It's not just about performance – it's about enabling entirely new approaches to biological discovery that were previously impossible."

Xiaoming Zhang

VP of Technology at Biomap

Whenever we demonstrate our solution with Milvus, we’re effectively crushing the cloud vendor solution’s performance. It’s a great benchmark because most enterprise users already know the vendor solution, so the comparison is immediate."

Hanlian Lyu

a Product Owner and BI Expert at Volvo Cars

From a performance standpoint, Zilliz Cloud's retrieval speed far exceeds our existing system. We achieved approximately 70% reduction in retrieval latency, which translates to a 4-5x improvement in overall problem-solving time when we successfully match original questions. Whether measured by speed, cost, or overall value, Zilliz Cloud perfectly met our expectations."

Dr. Nick Yuan

CTO

The biggest immediate impact for the company would be the cost side of things. We were able to bring the estimated cost of our search cluster from above five digits a month to a significantly lower figure. That would be the biggest improvement for our company."

Su-Meng Yong

Engineering Team Lead

We don’t have any concern related to database operations anymore after adopting Zilliz Cloud. Before, we had a lot of troubles—memory suddenly wasn’t enough, we needed to scale up, we didn’t have auto-scaling. All of those things caused a lot of problems. The most obvious benefits for us are the management and the data ingestion. That’s very attractive."

Lixiang Li

the engineering team lead at JERA

The migration was incredibly smooth. Using the built-in tools, we were able to import our data from Pinecone with essentially one click. The technical support has also been excellent — our questions get resolved almost instantly, and the documentation, demos, and examples are thorough and easy to work with."

Technical Team

We believe AI is becoming a meaningful support layer for physicians, but the experience has to feel trustworthy, reliable, and seamless. Building that kind of product requires a strong foundation behind the scenes. Zilliz Cloud has helped us create that foundation as we continue to grow and serve hundreds of thousands of clinicians."

Jagath Kumar

Head of Performance Engineering at OpenEvidence

We believe AI agents will become a fundamental interface for how people work, learn, and make decisions, and that only happens if those systems can access real-world information with speed, precision, and trust. That’s what we’re building at Exa. Aside from web search, Exa also operates entity search, and Zilliz Cloud has been an important part of that journey, giving us the retrieval performance and operational simplicity we need to scale our entity search product quickly and confidently."

Jeffrey Wang

Co-founder of Exa

"Einer der größten Erfolge, die wir gesehen haben, ist die bessere Verarbeitung von Suchanfragen, die semantisch, aber nicht textuell relevant sind. Längere, eher gesprächsartige Suchanfragen haben sich ebenfalls drastisch verbessert.""

Heath Hohwald

Tech Leader and Search Manager, Consensus

KI bewegt sich von der Beantwortung einmaliger Fragen hin zu Agenten, die sich erinnern, was das KI-Gedächtnis zum Herzstück von KI-Produkten für Verbraucher macht. Zilliz Cloud bietet uns eine solide Grundlage, der wir für den agentischen Gedächtnisabruf in großem Maßstab vertrauen können, sodass sich unser Team auf Produktinnovation und Benutzererfahrung konzentrieren kann, statt auf die darunterliegende Infrastruktur."

Charles Liu

Co-founder & CTO, Plaud

Unsere Aufgabe ist es, die beste Forschung für alle auffindbar zu machen, die Consensus nutzen. Zilliz Cloud bietet unserem Research-Agent schnelle, hochwertige semantische Suche und erweitert damit direkt die Reichweite der Belege, auf die er zugreifen kann."

Christian Salem

Co-founder & Chief Product Officer, Consensus

Wähle die Größenordnung, bei der du am Ende landen wirst, nicht die, die du gerade hast. Verbraucherdaten wachsen schneller, als irgendjemand plant, und eine Migration in dieser Größenordnung ist schmerzhaft. Übergib die Retrieval-Infrastruktur an Spezialisten und setze deine eigenen Leute für das Produkt ein."

The engineering team, Plaud

The fully managed version really saves both my team and the developers a lot of time from having to deal with a lot of problems, a lot of self-managing of the cluster. And regarding latency — we went from an initial 100 milliseconds to now sub 30 to 50 milliseconds, a roughly 50% reduction while being able to maintain production throughput."

Su-Meng Yong

Engineering Team Lead