From Dev to Prod, Vector Database Made Easy

Vector database made easy
for companies at different stages
Bootstrapping, Fast Growth, Expansion

1. 1 | © Copyright 10/22/23 Zilliz1 | © Copyright 10/22/23 Zilliz
From Dev to Prod,
Vector Database Made Easy
Presented by: Charles Xie

2. Charles Xie

Founder and CEO of Zilliz,
Founder of the Milvus Project
●Board member of LF AI & Data,
Foundation and chairperson from 2020
to 2021
●Founding engineer of Oracle 12c cloud
database
●Master in Computer Science, University
of Wisconsin-Madison
2
●means zillions of zillions, pronunciate
as /ʼzilis/
●the company behind the Milvus project,
since 2018
●Series B, $113M funding

3. 3
Vector Database : making sense of unstructured data
2024
A vector database stores embedding vectors and allows for
semantic retrieval of various types of unstructured data.

4. 4
Milvus, OSS vector database since 2019
Originally created by Zilliz, hosted by the Linux Foundation
2024
28K
10000
GitHub Stars
Enterprise users
70M
Downloads
270
Contributors

5. Vector database made easy
for companies at different stages

6. GenAI company life cycle

7. Bootstrapping stage
●First to market
●Easy to use
●Prepare for future growth

8. 82024
Easy to start
●Pip-install on your laptop
●plug into your favorite AI dev tools
●push to production with a single line of code

9. 92024
Prepare for future growth
●Write your code once, and running everywhere, at
any scale
○API and SDK are all the same

Milvus Lite
●Embedded
●No server
installation
●Low footprint
Milvus
●Dedicated server
●High performance
●Easy to maintain
○K8S
○Docker


Zilliz Cloud
●Multi-tenancy
●High availability
●Data security
●Complianced
○SoC2
○GDPR

10. Growth stage
●ROI, Cost optimization
●Scalability

11. 112024
Status quo: expensive, not scalable
In memory
●Most of
other VDBs
●HNSW
●Expensive

12. 122024
Lower cost
In memory
●Most of
other VDBs
●HNSW
●Expensive

On Disk
●Up to 10x
lower cost

13. 132024
Lower cost
In memory
●Most VDBs
●HNSW
●Expensive

On Disk
●Up to 10x
lower cost



Object store
●Up to 50x
lower cost

14. Storage and computation separation

15. Milvus: decoupling computation and storage

16. 16 | © Copyright 10/22/23 Zilliz16 | © Copyright 10/22/23 Zilliz
hierarchical storage and caching

17. 17 | © Copyright 10/22/23 Zilliz17 | © Copyright 10/22/23 Zilliz
Data caching

18. 182024
Higher scalability

10B vectors
of 1536 dimensions
in a single Milvus/Zilliz Cloud
instance

19. 192024
Higher scalability

10B vectors
of 1536 dimensions
in a single Milvus/Zilliz Cloud
instance

100B vectors
in one of the largest deployment

20. Milvus architecture

21. Expansion stage
●Performance
●Avoid vendor lock in
○Move data when you want
●Multi-cloud
●Global availability

22. 222024
VectorDBBench : OSS framework for VDB benchmarking

https://github.com/zilliztech/VectorDBBench

23. 232024
Performance

24. 24
Multi-cloud: Zilliz Cloud is built atop of OSS Milvus
AWS, GCP, Azure

2024

25. Global availability: Zilliz Cloud has 20 availability zones
NA, EMEA, APAC

26. Vector database applications

27. 27
Retrieval-Augmented Generation RAG
2024
A technique that combines the
strength of retrieval-based and
generative models:
●Improve accuracy and relevance
●Eliminate hallucination
●Provide domain-specific
knowledge

28. 28
RAG : an economic perspective
2024
A business model that bridges public
data and private data
●Data sovereignty
●You can't and shouldn't give your
private data to others

29. 29
RAG Evolution
2024
RAG 1.0, last year
●text
●LLMs,
○GTP3.5, GPT4

30. 30
RAG Evolution
2024
RAG 1.0, last year
●text
●LLMs,
○GTP3.5, GPT4
RAG 2.0, this year
●image, video
●multi modality models
○GTP4o

31. 31
RAG Evolution
2024
RAG 1.0, last year
●text
●LLMs,
○GTP3.5, GPT4
RAG 2.0, this year
●image, video
●multi modality models
○GTP4o
RAG 3.0, next year?
●user behavior
●customized recommendation systems
○Merlin

32. More application scenarios of vector databases

33. Thank You !
Milvus
Open Source Self-Managed

github.com/milvus-io/milvus

Zilliz Cloud
SaaS Fully-Managed

zilliz.com/cloud