SQL Chat or Findly? A Comprehensive Review

Natural language SQL chats

Supports multiple database systems

User-friendly interface

Context-aware conversations

Community support via Discord

Connection settings stored locally

Allows follow-up corrections

User feedback mechanism

Previous chats remembered

Edits in real-time

Easy-to-use chatbot

Generates actionable data insights

No SQL or Python knowledge required

Uses natural language processing

Reduces Time To Insight (TTI)

Eliminates reliance on data professionals

Simplifies onboarding process

Saves software engineering time

Allows questions on Slack

Compatible with all SQL databases

Generates incorrect information occasionally

Potential for harmful instructions

Produces biased content occasionally

Stored in local browser only

Depends on user feedback

Requires follow-up corrections

Accuracy varies

Lacks APIs integration

Limited to SQL databases

Only works on Slack

No Python interpretation support

Possibly long chatbot response times

User-specific data interpretation issues

Lacks multi-platform support

No direct databank integration

Dependent on English proficiency

Limited onboarding efficiency improvements