Zilliz Named a Leader in the 2025 Vector Database Company Evaluation by 360Quadrants

The Vector Database Market Is Expanding Rapidly

The vector database market is growing fast as AI, machine learning, and large-language-model applications drive strong demand for high-performance similarity search, semantic retrieval, and real-time data processing. This growth is fueled by the explosion of unstructured and

high-dimensional data, increasing enterprise adoption of retrieval-augmented generation (RAG), and the need for scalable, low-latency, AI-native infrastructure across sectors, including finance, retail, healthcare, and technology.

 

Vector databases are becoming foundational infrastructure for modern AI workflows. They enable efficient embedding storage, hybrid search, and seamless integration with cloud-native and GPU-accelerated systems. North America currently leads the market, while Asia-Pacific is emerging as the fastest-growing region. Cloud-based and hybrid deployment models continue to gain traction due to their flexibility, scalability, and cost-effectiveness.

 

Zilliz is a global leader in vector database technology and the creator of Milvus, one of the world's most widely adopted open-source vector databases. Milvus is purpose-built for high-performance similarity search, semantic retrieval, and AI-driven applications at scale.

About the Evaluation

360Quadrants, powered by MarketsandMarkets™, evaluated several startups in their Vector Database Company Evaluation Report, 2025. The evaluation covered over 140 companies, with the top 14 categorized and recognized as quadrant leaders.

Companies were assessed across factors including revenue, geographic presence, growth strategies, investments, demand channels, and sales strategies. The main criteria for product footprint included:

• Type: Native vector databases, Multimodal vector databases
• Offering: Vector database solutions, Services
• Technology / AI Application: Natural Language Processing (NLP), Computer Vision, Recommendation Systems, Others
• Deployment: Cloud, On-premises
• Data Type: Simple text data, Hybrid & multimodal data, Advanced data (video, sensor, geospatial, 3D)
• Verticals: IT & ITeS, BFSI, Healthcare & Life Sciences, Retail & E-commerce, Media & Entertainment, Manufacturing & IIoT, Government & Defense, Transportation & Automotive, and others

Recent Product Milestones

Zilliz recently announced the general availability of Milvus 2.6.x on Zilliz Cloud, delivering major enhancements that make large-scale vector search faster, smarter, and more cost-efficient for production AI applications.

Key capabilities in Milvus 2.6.x include:

• Tiered storage, which dynamically moves data across hot (memory), warm (SSD), and cold (object storage) tiers based on access patterns — reducing storage costs by up to 87% and delivering significant overall TCO savings for large-scale deployments
• High-performance metadata filtering, accelerated up to 100x through JSON Shredding and JSON Path indexing — critical for RAG pipelines, recommendations, and multi-tenant applications
• Hybrid full-text and vector search with BM25-optimized full-text search that delivers up to 7x faster performance than Elasticsearch on selected datasets, unifying keyword and semantic retrieval in a single system
• Expanded data-type support, including spatial data, timezone-aware timestamps, INT8 vectors, and nested structures, alongside improved multilingual tokenization and phrase search

Beyond the core database engine, Zilliz Cloud has rapidly expanded its enterprise capabilities:

• Bring Your Own Cloud (BYOC) is now available across all three major cloud platforms — AWS, GCP, and Azure — making Zilliz the first managed vector database to offer BYOC on every major cloud. This lets enterprises run a fully managed vector database inside their own cloud accounts, preserving data residency, governance, and existing cloud commitments.
• Global Cluster with cross-region disaster recovery provides region-level resilience using real-time Change Data Capture (CDC) replication, automatic failover in under 60 seconds, and a single Global Endpoint that reroutes traffic transparently — without code changes.
• Semantic and text highlighter tools enable sentence-level relevance filtering and keyword highlighting in search results, helping reduce RAG token costs and improve answer quality.
• Intelligent replica autoscaling adjusts replica counts in real time based on workload metrics, eliminating manual capacity planning.

Together, these updates reinforce Zilliz Cloud as a fully managed, enterprise-ready vector database service that brings the power of open-source Milvus to cloud environments with enhanced automation, cost control, and AI-centric search functionality.

Zilliz's Strategic Pillars

Zilliz's strategic approach rests on five fundamental pillars:

Open-Source Leadership

Zilliz anchors its strategy around Milvus, the widely adopted open-source vector database. This builds developer trust, accelerates innovation, and cultivates a strong global community. Open source also drives enterprise adoption by reducing the risk of vendor lock-in.

AI-First, Vector-Native Architecture

The company focuses exclusively on AI workloads — semantic search, recommendation systems, and RAG for large language models. Its vector-native design is optimized for high-dimensional embeddings, enabling fast similarity search at massive scale and aligning Zilliz directly with the GenAI ecosystem.

Cloud-Native Managed Services

Zilliz complements its open-source offering with Zilliz Cloud, a fully managed cloud service. This lowers operational complexity for enterprises by providing scalability, high availability, and performance without infrastructure overhead, while supporting hybrid and multi-cloud deployment strategies.

Performance, Scalability, and Cost Efficiency

Delivering low-latency, high-throughput vector search across billion-scale datasets is a core pillar. Zilliz invests in hardware acceleration, indexing innovation, and efficient storage to keep the platform enterprise-ready and cost-effective for real-time AI applications.

Ecosystem and Enterprise Integration

Zilliz prioritizes integration with popular AI frameworks, LLM stacks, and data platforms. This ecosystem-driven strategy ensures seamless adoption across AI pipelines, while strong enterprise features — security, governance, and compliance — support production use cases.

Final Thoughts

Zilliz has evolved from a vector database provider into a core enabler of AI-driven applications. Through continued leadership in open-source Milvus and the expansion of Zilliz Cloud, the company demonstrates a balanced strategy of innovation and enterprise readiness.

Its strong focus on GenAI, RAG, and real-time semantic search reflects deep alignment with emerging industry needs. An emphasis on scalability, low latency, and cost efficiency highlights both technical depth and production maturity. Zilliz's cloud-native, developer-friendly approach lowers adoption barriers for organizations at any scale, and robust ecosystem integrations further strengthen its position within modern AI stacks.

Overall, Zilliz presents a clear, future-oriented vision: to make vector search a reliable foundation for next-generation AI systems.

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