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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

4.7K visits/mo

Thin 'Lingbot-map' agent listing on github.com with zero traffic; too thin to tell.

5.2K saves
Gemini Code Assist logo
Gemini Code Assist
✓ verifiedFreemium

Google's AI coding assistant for code completion, generation, chat and review across IDEs and GitHub.

559K visits/mo
Text2SQL logo
Text2SQL
✓ verifiedPaid

AI tool that converts natural-language questions into SQL queries, sold via a Lemon Squeezy storefront with tiered pricing.

20K visits/mo14K saves
Sequel logo
Sequel
✓ verifiedFreemium

Governed data layer connecting marketing, product and finance sources to AI agents for plain-language querying.

6.4K visits/mo4.3K saves
Pricing

No public pricing

No public pricing

No public pricing

Text2SQL.AI: $7.00-$48.00
Text2SQL.AI Pro: $29.00-$228.00

Free trial available

Free: $0/mo (1 data source, 1 user)
Pro: $19/mo (unlimited data sources, 1 user)
Team: $99/mo (unlimited data sources and users, Slack access)
Core features
  • Zero-ETL data integration
  • Federated Query
  • Streaming Ingestion
  • Instant Replication with CDC
  • API to SQL conversion
  • NoSQL to SQL conversion
  • SQL to API conversion
  • Self-service Integration
  • Generate SQL with AI
  • 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 code completion and suggestions
  • Natural-language code generation
  • In-IDE chat assistance
  • AI code review
  • IDE integrations (VS Code, JetBrains, etc.)
  • GitHub integration
  • Natural language to SQL query generation
  • Standard and Pro subscription tiers
  • Checkout and billing via Lemon Squeezy
  • Unified connection to 100+ marketing/product/finance data sources
  • MCP-compatible interface usable by any AI agent
  • Learns custom metric definitions and joins across sources
  • Secure credential gateway that keeps raw keys from agents
  • Cross-source joins spanning databases, warehouses and product data
  • Fine-grained audit logs of every query
  • Live dashboards and debugging in plain English
Use cases
  • Query data directly from its source in real-time.
  • Process data wherever it is, blending data from different sources.
  • Ingest streaming data from Kafka, Segment, etc., into Peaka BI Table.
  • Replace nightly batch ingestion with real-time data access.
  • Treat every data source like a relational database by converting APIs to tables.
  • Use SQL to query NoSQL databases.
  • Query consolidated data and expose it with APIs.
  • Creating and manipulating datasets
  • Training small machine learning models
  • Implementing advanced training and inference logic
  • Building applications that require tensor computations
  • Speeding up coding with AI completions
  • Generating code from plain-language prompts
  • Getting in-editor help and explanations
  • Reviewing pull requests with AI
  • Understanding unfamiliar codebases
  • Generating SQL queries without writing raw syntax
  • Helping non-technical users query databases
  • Speeding up ad hoc data lookups for analysts
  • Marketing teams asking AI agents for campaign or ROAS reports
  • Data teams governing access to metrics across tools
  • Agencies building AI-driven client reporting
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