BerriAI/litellm - GitHub vs Chat With Data

Side-by-side comparison · Updated October 2026

 BerriAI/litellm - GitHubBerriAI/litellm - GitHubChat With DataChat With Data
DescriptionLiteLLM is an AI gateway and Python SDK from Berrie AI Incorporated, published in the BerriAI GitHub repository. The SDK provides a common interface for model calls inside Python applications. The proxy gateway centralizes access for a team, with virtual keys, model routing, spend tracking, budgets and an administration interface. The official documentation lists support for more than 100 model providers. Supported endpoints and features vary by integration, so verify your model’s streaming, tool-calling, image, audio or embedding requirements. The router supports retries, fallbacks and load balancing; observability integrations can send request data to tools such as Langfuse, LangSmith and OpenTelemetry. LiteLLM also provides an MCP gateway. It can connect upstream servers using Streamable HTTP, SSE or stdio, expose tools through a fixed gateway endpoint, and scope access by key, team or organization. This requires configuring the upstream servers and authentication; the gateway does not automatically grant access to third-party tools. Agent-to-agent integrations are documented separately. The open-source offering has no software license fee for self-hosting. Code outside the enterprise directory is MIT-licensed, while enterprise code has separate terms. Enterprise pricing is quoted by annual gateway request capacity, deployment architecture and support needs, rather than a per-token license charge. Model-provider charges and infrastructure costs still apply. Enterprise adds controls and support such as SSO, SCIM, audit logs and service-level agreements. Compare New API for another self-hosted gateway with provider-channel management and usage accounting. Evaluate a representative workload, inspect request logging and secret handling, test budget and failure behavior, and decide whether SDK integration or a shared gateway best fits your application.Chat With Data, also known as DataChat, is a no-code generative AI analytics platform designed for business users and domain experts to extract insights from data seamlessly. By using plain English queries instead of complex programming languages, it eliminates the need for technical skills, allowing easy access to data analysis. Key features include its intuitive no-code interface, transparency in analytical steps, and iterative analytics process. It integrates with platforms like Google BigQuery and HubSpot for varied data handling and supports industries like finance, sales, marketing, and customer service in data-driven decision-making.
CategoryDeveloper ToolsData Analytics
RatingNo reviewsNo reviews
PricingOpen SourcePricing unavailable
Starting PriceN/AN/A
Use Cases
  • Developers
  • Enterprises
  • Startups
  • Educational Institutions
  • Financial analysts
  • Sales teams
  • Marketing professionals
  • Customer service managers
Tags
AI gatewayPython SDKLLM routingMCP gatewayvirtual keys
no-codeAI analyticsdata insightsbusiness usersdomain experts
Features
Python SDK for direct application integration
Shared AI proxy gateway and administration UI
More than 100 documented model-provider integrations
Virtual keys, users, teams, budgets and rate limits
Spend tracking and observability integrations
Router retries, fallbacks and load balancing
MCP gateway for Streamable HTTP, SSE and stdio upstreams
Key, team and organization MCP permissions
Separate enterprise identity, audit and support features
Natural language interaction
User-friendly interface
Real-time data processing
Integration with multiple data sources
Intelligent data analysis
Comprehensive data visualization
Customizable queries
Large dataset support
Secure data handling
 View BerriAI/litellm - GitHubView Chat With Data

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