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✓ verifiedFreemium
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
775K visits/mo
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Project IDX by Google
✓ verifiedFree
Google's cloud-based, AI-assisted development environment, now rebranded and merged into Firebase Studio.
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Tabnine AI
✓ verifiedPaid
Enterprise-focused AI coding assistant offering code completion, in-IDE chat and agentic workflows with strict code privacy controls.
Pricing
No public pricing
No public pricing
No public pricing
AI Coding Platform: $39 per user per month (annual subscription)
No public pricing
Core features
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Cloud-based IDE accessible from the browser
- ✦AI-assisted coding
- ✦Cross-platform app development
- ✦Preconfigured workspaces and templates
- ✦Now part of Firebase Studio
- ✦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 for single and multi-line suggestions
- ✦In-IDE chat supporting the full software development lifecycle
- ✦Agentic workflows and a CLI for terminal-based AI coding
- ✦Enterprise Context Engine for org-specific codebase understanding
- ✦Zero code retention and no training on customer code
- ✦Flexible deployment: SaaS, VPC, on-prem or air-gapped
- ✦Governance controls, SSO, and centralized usage analytics
- ✦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
Use cases
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Building apps from anywhere in the browser
- →Prototyping with AI assistance
- →Developing cross-platform applications
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Enterprise engineering teams needing private, compliant AI coding tools
- →Developers wanting AI chat and completions inside their existing IDE
- →Organizations with legacy or mixed tech stacks requiring context-aware suggestions
- →Security-sensitive teams requiring air-gapped AI deployment
- →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.
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