Velvet or Text2SQL? A Comprehensive Review

Transforms team into data engineers

Enables data query from disparate sources

Offers real-time feature shipping

Allows complex SQL writing

Facilitates large data parsing

Turns queries into visual data

Data stored as query API endpoints

Supports real-time data for product development

Permits ingestion of any data source

Allows access to queries as API endpoints

Supports multiple SQL dialects

Can connect custom database schema

Free to use

Ideal for beginners and professionals

Generates SQL queries quickly

Cost-effective compared to similar tools

Allows SQL explanation to plain English

Supports a broad range of queries

Supports CREATE and ALTER TABLE requests

Supports constraints

Limited to high-growth startups

No explicit support for non-SQL languages

Real-time data might affect performance

Possible user overwhelm with unlimited data

Could favor tech-savvy users

No offline mode mentioned

Lack of data backup mechanisms

No explicit data security measures

Limited to GPT-3 Codex

No API provided

Questionable accuracy

Not ideal for advanced usage

Dependent on BETA phase

Lacks performance optimization

May require manual checking

No real-time support

Doesn't support all SQL features