RaBitQ, JSON Index, Schema Evolution, What's New in Milvus 2.6

1 | © Copyright 2025 Zilliz
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Jiang Chen @ Zilliz
Whatʼs New in Milvus 2.6

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2 | © Copyright 9/6/23 Zilliz
Jiang Chen
Head of Developer Relations
jiang.chen@zilliz.com
https://www.linkedin.com/in/jiangc1010/
https://x.com/jiangc1010

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Prototype
Quality
Optimization
Productionisation

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The Problem Space of Search Serving

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The Problem Space of Search Serving
Where infrastructure
challenge arise

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Milvus is an Open-Source Vector Database to
store, index, manage, and use massive number
of vector embeddings for information retrieval.
contributors
300
stars
38K
active pods
100M
forks
3.3K+
Milvus: Built for Production

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Milvus 2.6 at a Glance
Lower
Infrastructure
Costs
Boost Developer
Productivity
Consistent
Performance
New
Architecture

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In-memory Index with Quantization

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Vector Quantization

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RaBitQ
RaBitQ is a binary quantization method based on the geometric properties of
high-dimensional space.
Much better recall than vanilla binary quantization methods.

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RaBitQ

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Tiered Storage
• Tiered Storage (hot/cold data)
• LRU Cache
Cache
Management

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Busting the Ingestion Bottleneck
X
X

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Architecture Evolvement to Scale Beyond Billions
✔ Alternative to Kafka or Pulsar: Streaming Node + WoodPecker
✔ Merge IndexNode and DataNode
✔ Merge All Coordinator into MixCoord

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New Architecture to Scale Streaming Ingestion

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Embedding and Reranker Models as UDF

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More Sophisticated Search Pipelines
Hybrid retrieval with dense vector search and full-text search

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Better Full-Text Search
✔ Multi Language Tokenizer
✔ Phrase Match
✔ Time-Aware Decay Functions
✔ Boost Ranker

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Milvus Data Model - Struct List
Primary Key Partition Key Dedicated Fields Dynamic Field Vector Fields ROW ID Timestamp
Reserved by the System
● Uniquely identifies
an entity
● Varchar or Int64
● User defined or
auto-generated
● Optional
● User defined or
auto-generated
● Optimizes search
by narrowing
queries to relevant
partitions
● Pre-defined
● Supported data
types: Numeric,
Varchar, JSON,
Array
● Roadmap support
for: Set,
Geolocation
● Supports optional
fields without
schema changes
● Stored as key-value
pairs
● Allows scalar
filtering on dynamic
fields
● Stored in a JSON
string
● Dense Float32,
Float16, BFloat16
● Sparse
● Binary
● 10 vector fields per
entity can be
defined
● Used as
Multi-Version
Concurrency
Control MVCC) and
concurrency
guarantee
The same data model for
for Milvus Lite, Standalone,
Distributed and Zilliz Cloud

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More Flexible Schema and Better Index
✔ Add Field Support for Schema Evolution
✔ JSON Shredding and JSON Index
✔ Ngram Index
✔ MinHash LSH Index for Large Scale Data Deduplication
✔ Embedding List (coming soon)

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Json Shredding
{"a":10,"b":"str1","d":"42", f:1}
{"a":20,"b":"str2","d":"43", f:2}
{"a":30,"b":"str3","e":"44"，f:3}
{"a":40,"b": 1,"d":"foo","e":"baz"}
{"a":50,"b": 2,"d":["23","24"]}
{"a":60,"b": 3,"d":{"e":"bar"},"e":"45"}
Performance Improvement 10100x
in our dynamic field test

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One Last Thing

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Milvus Evolvement
2.0
2.5
2.6
3.0
Filtered
Search
Full-text
Search
Tiered
Storage
?
Lake!

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Multimodal Lake
Data Cleaning Label
Extraction
Data Mining, Iterative Search

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Use Case: Iterative Search in Training Data Curation
“A frame with a blue bus and a motorcycle”

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Milvus Vector Lake Ecosystem

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Thank you!
github.com/milvus-io/milvus zilliz.com/learn/generative-ai

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Two Stages of AI Search Development
Thrive with great search quality
Consistently deliver the best performance
at scale

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A New tool emerged. The Vector Database
🔍

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Retrieval Augmented Generation RAG

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Search / Recommendation System

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Agent Memory
Milvus as the central information repository for agentic workflow

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Knowledge Entity Extraction

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Structured Label Extraction
https://github.com/google/langextract

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BUILT FOR AI OPEN SOURCE Performant at Scale
Why Milvus
Designed from the ground
up for vector search
Fully open source under
Apache 2.0, no vendor lock-in
Handles billions of vectors
with sub-10ms latency
Check Fully Managed Milvus at zilliz.com

RaBitQ, JSON Index, Schema Evolution, What's New in Milvus 2.6

RaBitQ, JSON Index, Schema Evolution, What's New in Milvus 2.6

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