Compare tools
Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
⇄ Comparison dimension — pick the market you're actually shopping in
✕
Sherloq
✓ verifiedFreemium
AI chat assistant for analysts that generates and fixes SQL using an organization's own saved query history.
12K visits/mo
✕
EverSQL
✓ verifiedFree
AI-powered SQL optimizer for PostgreSQL and MySQL that auto-rewrites and indexes queries; now free as part of Aiven.
6.5K visits/mo
Pricing
DEVELOPER: FREE
STARTER: $119 / month
GROWTH: $599 / month
ENTERPRISE: Starting at $1,800 / month
No public pricing
No public pricing
No public pricing
No public pricing
Core features
- ✦Developer-first platform for AI-powered integrations
- ✦Secure, isolated sandboxes for running JavaScript/Python code
- ✦Automatic management of npm/PyPI dependencies
- ✦Built-in platform plumbing: secrets, webhooks, scheduling, logs, and audit
- ✦Yep Agent (prompt → runnable processes)
- ✦MCP Server/Tools (convert code into AI agent tools)
- ✦Serverless runtime (YepCode Run) and SDK access
- —
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦AI chat trained on the user's own SQL repository
- ✦query saving, tagging, and versioning
- ✦team folder permissions and sharing
- ✦Chrome extension and IntelliJ plugin
- ✦SOC2-compliant security with no database access needed
- ✦table and field lookup assistance
- ✦Automatic SQL query optimization
- ✦Query rewriting and indexing suggestions
- ✦Non-intrusive performance sensor
- ✦Ongoing performance insights
- ✦Database cost-reduction recommendations
- ✦PostgreSQL and MySQL support
Use cases
- →Building complex API integrations that require custom code and logic beyond what no-code tools offer.
- →Safely running AI-generated scripts in isolated environments with secrets management.
- →Automating workflows that require large datasets, loops, branching, or custom dependencies.
- →Connecting AI agents to external databases, APIs, and services using MCP tools.
- —
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →sharing reusable SQL snippets across an analytics team
- →quickly fixing syntax errors in existing queries
- →onboarding new analysts to a team's existing SQL logic
- →building a searchable personal or team SQL knowledge base
- →Optimizing slow SQL queries
- →Monitoring database performance
- →Reducing database CPU and storage costs
- →Getting indexing recommendations
Visit