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Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Online database-design tool with sample schemas and an AI generator to explore, modify or build database structures visually.
Low-code integration platform for connecting thousands of APIs into workflows and AI agents, including an MCP tool server.
Vibe-coding builder creating full-stack apps by chatting with AI.
Open-source asset-based data orchestrator, with Dagster+ cloud, for building, observing and delivering reliable data and AI pipelines.
No public pricing
No public pricing
No public pricing
Free trial available
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Library of sample database designs
- ✦Visual database designer / diagram tool
- ✦AI database generator
- ✦Modify and optimize existing schemas
- ✦SQL script export
- ✦Dialect converters (MySQL/PostgreSQL/MSSQL)
- ✦Visual and code-based workflow builder
- ✦Prebuilt AI agent builder and deployment
- ✦Managed authentication across thousands of apps
- ✦MCP server exposing integrations as agent tools
- ✦Scheduled and event-triggered workflows
- ✦Connect SDK for embedding integrations into other products
- ✦CodeFlying enables full-stack app creation via chat in minutes
- ✦Asset-based pipeline orchestration
- ✦Built-in lineage and data-quality checks
- ✦Data catalog with asset metadata
- ✦Native dbt, Snowflake and Fivetran integrations
- ✦Branch deployments and hybrid deployment
- ✦Open-source core plus managed Dagster+ cloud
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Finding a starting schema for a project
- →Designing a database visually
- →Generating a schema with AI
- →Converting between SQL dialects
- →Building AI agents that call external APIs and tools
- →Automating cross-app workflows such as Slack, Gmail, or Sheets notifications
- →Embedding third-party integrations into a SaaS product
- →Prototyping event-driven automations without heavy infrastructure
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- →Orchestrate ETL/ELT and dbt pipelines
- →Monitor data health and lineage
- →Build AI/ML data pipelines
- →Run reliable, observable data platforms