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TheSQL Vector Database for Scalable AI
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MYSCALE
Enable every developer to build production-grade GenAI applications with powerful and familiar SQL. Minimal Learning, Max Value,
and Cost-Effective.
Trusted SQL/Integrated Vector Database









Fully SQL-Compatible Vector Database
Fast and Powerful Queries
Perform fast, powerful, and efficient vector search, text search, filtered search, and SQL-vector join queries.
Vector search
Text search
Filtered search
Complex queries
-- Create MSTG index on vector column for arxiv_table
ALTER TABLE doc_table
ADD VECTOR INDEX vec_idx vector
TYPE MSTG('metric_type=Cosine');
-- Perform vector search and return top 10 results
SELECT
id, title, text
distance(vector, query_vector) as dist
FROM doc_table
ORDER BY
dist ASC
LIMIT 10;
Manage All Types of Data
Data Import & Export
Integrate with Your Stack
Start Free TrialTry Playground
Vector search
Text search
Filtered search
Complex queries
-- Create MSTG index on vector column for arxiv_table
ALTER TABLE doc_table
ADD VECTOR INDEX vec_idx vector
TYPE MSTG('metric_type=Cosine');
-- Perform vector search and return top 10 results
SELECT
id, title, text
distance(vector, query_vector) as dist
FROM doc_table
ORDER BY
dist ASC
LIMIT 10;
Enhanced RAG Effectiveness
- Achieve superior RAG (Retrieval-Augmented Generation) results
- Combine vector and full-text search for thorough data retrieval
- Utilize advanced metadata filtering for precise outcomes
- Adapt to changing business requirements with flexible data modeling
High-Performance and Cost-Efficient
- 3x the speed, 3x the savings with
MSTG vector engine - Performant & powerful metadata filter search
- Faster data ingestion with optimized index building
SQL/Relational Vector Database
- Manage and query AI-related data within a single system
- Execute advanced SQL vector joint queries
- Enable text-to-SQL translation for complex querying needs
Powerful Full-Text Search
- BM25 for enhanced relevance ranking
- Configurable tokenizers for various languages
- Simple yet powerful query language
Integrates with Your AI Stack
- Deep integration with popular development languages and frameworks
- Seamless LLM application observability with
MyScale Telemetry
Security and Compliance
SQL-based RBAC
In compliance with SOC 2
ISO 27001 Compliance
The Generative AI Stack
Build and deliver quickly with the best integrations and tools
Work seamlessly with tools and popular languages adopted by leading Generative AI enterprises and LLM developers
AI integrations
Language SDK
File formats
Functions
Build Your AI Apps with MyScale
\
RAG for Domain Knowledge Base
\
Recommendations
\
Chatbot
\
Image Search
Why Industry Leaders Choose MyScale
MyScale's support for SQL is just amazing! It enables developers who are familiar with SQL but not vector search to quickly get
started. You won't have this kind of user experience in other products. Additionally, for production-level applications, MyScale
has significantly reduced our costs.
We have previously tried vector solutions like Pinecone, PgVector, Chroma, Zilliz, and Redis. We are very impressed by the
user-friendliness of MyScale and its seamless integration with Langchain.

MyScale's performance in memory resource optimization and data insertion efficiency far surpasses our previous solution.

The self-developed MSTG index by MyScale has helped us resolve many issues. Additionally, in the application of Text to SQL
integration, MyScale has demonstrated essential compatibility. We are truly grateful for the assistance and suggestions provided
by MyScale.

FAQs
Your quick start guide to getting to know MyScale. We are here for you - reach out through the provided channels, and let's
chat.
What is the difference between MyScale and a specialized vector database?
What types of vector data does MyScale support?
What is the difference between traditional search and vector search?
Can I easily migrate from PostgreSQL to MyScale?
Is MyScale available as a managed database service?
How does MyScale perform?
Does MyScale have a RAG (Retrieval-Augmented Generation) solution? Where can I find a demo?
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SQL Vector Databases are Shaping the New LLM and Big Data Paradigm
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