vulcan-sql
Data API Framework for AI Agents and Data Apps
Stars: 592
VulcanSQL is an Analytical Data API Framework for AI agents and data apps. It aims to help data professionals deliver RESTful APIs from databases, data warehouses or data lakes much easier and secure. It turns your SQL into APIs in no time!
README:
VulcanSQL is an Analytical Data API Framework for AI agents and data apps. It aims to help data professionals deliver RESTful APIs from databases, data warehouses or data lakes much easier and secure. It turns your SQL into APIs in no time!
Given the vast amount of analytical data in databases, data warehouses, and data lakes, there is currently no easy method for data professionals to share data with relevant stakeholders for operational business use cases.
Without a specialized framework to streamline the creation of APIs for AI agents and apps to interact with databases and data warehouses, developers today must undertake a more manual and complex process. This approach comes with several pain points and challenges:
- Time-Consuming: Developers need to manually code the APIs, which can be time-consuming, especially for complex applications or when dealing with multiple data sources.
- Error-Prone: Manual coding increases the risk of bugs and errors, which can affect the reliability and performance of the APIs.
- Diverse Data Sources: Integrating multiple data sources with different formats and protocols requires significant effort and expertise.
- Lack of Standardization: Without a standardized approach, each API might follow different conventions, making it harder for AI agents to interact with them consistently.
- Security Risks: Ensuring that APIs are secure and that data access complies with regulations (e.g., GDPR, HIPAA) requires additional layers of work, including authentication, authorization, and data encryption.
- Maintenance Overhead: Security and compliance requirements can evolve, necessitating ongoing maintenance and updates to the APIs.
- Scalability Concerns: Custom-built APIs may not be optimized for scalability, leading to performance issues as the number of requests or the volume of data grows.
- Resource Intensive: Optimizing for performance and scalability can require significant resources, both in terms of development time and infrastructure.
- Lack of Documentation: Properly documenting APIs for easy understanding and use by other developers or AI agents can be overlooked or undervalued.
- Usability Issues: Without clear and comprehensive documentation, it becomes challenging for others to integrate with and effectively use the APIs.
-
Rapid Development and Integration: By abstracting the complexities of directly interacting with databases and data warehouses, developers can focus on the higher-level logic of their applications. This reduces the development time and simplifies the process of integrating AI capabilities into applications.
-
Standardization: Utilizing OpenAPI documents for interaction provides a standardized way for AI agents to understand and interact with different APIs. This promotes interoperability among various systems and tools, making it easier to integrate with a wide array of services and data sources.
-
Scalability and Maintenance: A template-driven approach to API creation can make it easier to scale and maintain APIs over time. Changes in the underlying data schema or business logic can be propagated to the APIs more efficiently, without the need for extensive manual adjustments.
-
Accessibility: Making data more accessible to AI agents through well-defined APIs can unlock new insights and capabilities by leveraging machine learning and analytics. This can enhance decision-making processes and automate routine tasks, among other benefits.
Use Online Playground to get a taste of VulcanSQL!
Please visit the installation guide.
Need inspiration? Here are a selected compilation of examples showcasing how you can use VulcanSQL!
💻 Build
VulcanSQL offers a development experience similar to dbt. Just insert variables into your templated SQL. VulcanSQL accepts input from your API and generates SQL statements on the fly.
🚀 Accelerate
VulcanSQL uses DuckDB as a caching layer, boosting your query speed and reducing API response time. This means faster, smoother data APIs for you and less strain on your data sources.
🔥 Deploy
VulcanSQL offers flexible deployment options - whether you prefer Docker or command-based setups. Our package command assists in bundling your assets, ensuring a smooth transition from development to deployment of your data APIs.
❤️ Share
VulcanSQL offers many data sharing options, seamlessly integrating your data into familiar applications within your workflow and build AI agents.
Below are some common scenarios that you may be interested:
🤖 AI agents: Streamline the creation of APIs for AI agents to interact with databases and data warehouses.
📈 Customer-facing analytics: Expose analytics in your SaaS product for customers to understand how the product is performing for them via customer dashboards, insights, and reports.
👏 Data sharing: Sharing data with partners, vendors, or customers, which requires a secure and scalable way to expose data.
⚙️ Internal tools: Integration with internal tools like Zapier, AppSmith and Retools, etc.
- If there is any issues, please visit Github Issues.
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for vulcan-sql
Similar Open Source Tools
vulcan-sql
VulcanSQL is an Analytical Data API Framework for AI agents and data apps. It aims to help data professionals deliver RESTful APIs from databases, data warehouses or data lakes much easier and secure. It turns your SQL into APIs in no time!
akeru
Akeru.ai is an open-source AI platform leveraging the power of decentralization. It offers transparent, safe, and highly available AI capabilities. The platform aims to give developers access to open-source and transparent AI resources through its decentralized nature hosted on an edge network. Akeru API introduces features like retrieval, function calling, conversation management, custom instructions, data input optimization, user privacy, testing and iteration, and comprehensive documentation. It is ideal for creating AI agents and enhancing web and mobile applications with advanced AI capabilities. The platform runs on a Bittensor Subnet design that aims to democratize AI technology and promote an equitable AI future. Akeru.ai embraces decentralization challenges to ensure a decentralized and equitable AI ecosystem with security features like watermarking and network pings. The API architecture integrates with technologies like Bun, Redis, and Elysia for a robust, scalable solution.
seatunnel
SeaTunnel is a high-performance, distributed data integration tool trusted by numerous companies for synchronizing vast amounts of data daily. It addresses common data integration challenges by seamlessly integrating with diverse data sources, supporting multimodal data integration, complex synchronization scenarios, resource efficiency, and quality monitoring. With over 100 connectors, SeaTunnel offers batch-stream integration, distributed snapshot algorithm, multi-engine support, JDBC multiplexing, and log parsing. It provides high throughput, low latency, real-time monitoring, and supports two job development methods. Users can configure jobs, select execution engines, and parallelize data using source connectors. SeaTunnel also supports multimodal data integration, Apache SeaTunnel tools, real-world use cases, and visual management of jobs through the SeaTunnel Web Project.
dapr-agents
Dapr Agents is a developer framework for building production-grade resilient AI agent systems that operate at scale. It enables software developers to create AI agents that reason, act, and collaborate using Large Language Models (LLMs), while providing built-in observability and stateful workflow execution to ensure agentic workflows complete successfully. The framework is scalable, efficient, Kubernetes-native, data-driven, secure, observable, vendor-neutral, and open source. It offers features like scalable workflows, cost-effective AI adoption, data-centric AI agents, accelerated development, integrated security and reliability, built-in messaging and state infrastructure, and vendor-neutral and open source support. Dapr Agents is designed to simplify the development of AI applications and workflows by providing a comprehensive API surface and seamless integration with various data sources and services.
fridon-ai
FridonAI is an open-source project offering AI-powered tools for cryptocurrency analysis and blockchain operations. It includes modules like FridonAnalytics for price analysis, FridonSearch for technical indicators, FridonNotifier for custom alerts, FridonBlockchain for blockchain operations, and FridonChat as a unified chat interface. The platform empowers users to create custom AI chatbots, access crypto tools, and interact effortlessly through chat. The core functionality is modular, with plugins, tools, and utilities for easy extension and development. FridonAI implements a scoring system to assess user interactions and incentivize engagement. The application uses Redis extensively for communication and includes a Nest.js backend for system operations.
deepflow
DeepFlow is an open-source project that provides deep observability for complex cloud-native and AI applications. It offers Zero Code data collection with eBPF for metrics, distributed tracing, request logs, and function profiling. DeepFlow is integrated with SmartEncoding to achieve Full Stack correlation and efficient access to all observability data. With DeepFlow, cloud-native and AI applications automatically gain deep observability, removing the burden of developers continually instrumenting code and providing monitoring and diagnostic capabilities covering everything from code to infrastructure for DevOps/SRE teams.
trustgraph
TrustGraph is a tool that deploys private GraphRAG pipelines to build a RDF style knowledge graph from data, enabling accurate and secure `RAG` requests compatible with cloud LLMs and open-source SLMs. It showcases the reliability and efficiencies of GraphRAG algorithms, capturing contextual language flags missed in conventional RAG approaches. The tool offers features like PDF decoding, text chunking, inference of various LMs, RDF-aligned Knowledge Graph extraction, and more. TrustGraph is designed to be modular, supporting multiple Language Models and environments, with a plug'n'play architecture for easy customization.
llmariner
LLMariner is an extensible open source platform built on Kubernetes to simplify the management of generative AI workloads. It enables efficient handling of training and inference data within clusters, with OpenAI-compatible APIs for seamless integration with a wide range of AI-driven applications.
JamAIBase
JamAI Base is an open-source platform integrating SQLite and LanceDB databases with managed memory and RAG capabilities. It offers built-in LLM, vector embeddings, and reranker orchestration accessible through a spreadsheet-like UI and REST API. Users can transform static tables into dynamic entities, facilitate real-time interactions, manage structured data, and simplify chatbot development. The tool focuses on ease of use, scalability, flexibility, declarative paradigm, and innovative RAG techniques, making complex data operations accessible to users with varying technical expertise.
Upsonic
Upsonic offers a cutting-edge enterprise-ready framework for orchestrating LLM calls, agents, and computer use to complete tasks cost-effectively. It provides reliable systems, scalability, and a task-oriented structure for real-world cases. Key features include production-ready scalability, task-centric design, MCP server support, tool-calling server, computer use integration, and easy addition of custom tools. The framework supports client-server architecture and allows seamless deployment on AWS, GCP, or locally using Docker.
apo
AutoPilot Observability (APO) is an out-of-the-box observability platform that provides one-click installation and ready-to-use capabilities. APO's OneAgent supports one-click configuration-free installation of Tracing probes, collects application fault scene logs, infrastructure metrics, network metrics of applications and downstream dependencies, and Kubernetes events. It supports collecting causality metrics based on eBPF implementation. APO integrates OpenTelemetry probes, otel-collector, Jaeger, ClickHouse, and VictoriaMetrics, reducing user configuration work. APO innovatively integrates eBPF technology with the OpenTelemetry ecosystem, significantly reducing data storage volume. It offers guided troubleshooting using eBPF technology to assist users in pinpointing fault causes on a single page.
doris
Doris is a lightweight and user-friendly data visualization tool designed for quick and easy exploration of datasets. It provides a simple interface for users to upload their data and generate interactive visualizations without the need for coding. With Doris, users can easily create charts, graphs, and dashboards to analyze and present their data in a visually appealing way. The tool supports various data formats and offers customization options to tailor visualizations to specific needs. Whether you are a data analyst, researcher, or student, Doris simplifies the process of data exploration and presentation.
postgresml
PostgresML is a powerful Postgres extension that seamlessly combines data storage and machine learning inference within your database. It enables running machine learning and AI operations directly within PostgreSQL, leveraging GPU acceleration for faster computations, integrating state-of-the-art large language models, providing built-in functions for text processing, enabling efficient similarity search, offering diverse ML algorithms, ensuring high performance, scalability, and security, supporting a wide range of NLP tasks, and seamlessly integrating with existing PostgreSQL tools and client libraries.
latitude-llm
Latitude is an open-source prompt engineering platform that helps developers and product teams build AI features with confidence. It simplifies prompt management, aids in testing AI responses, and provides detailed analytics on request performance. Latitude offers collaborative prompt management, support for advanced features, version control, API and SDKs for integration, observability, evaluations in batch or real-time, and is community-driven. It can be deployed on Latitude Cloud for a managed solution or self-hosted for control and customization.
AgentForge
AgentForge is a low-code framework tailored for the rapid development, testing, and iteration of AI-powered autonomous agents and Cognitive Architectures. It is compatible with a range of LLM models and offers flexibility to run different models for different agents based on specific needs. The framework is designed for seamless extensibility and database-flexibility, making it an ideal playground for various AI projects. AgentForge is a beta-testing ground and future-proof hub for crafting intelligent, model-agnostic autonomous agents.
For similar tasks
vulcan-sql
VulcanSQL is an Analytical Data API Framework for AI agents and data apps. It aims to help data professionals deliver RESTful APIs from databases, data warehouses or data lakes much easier and secure. It turns your SQL into APIs in no time!
olah
Olah is a self-hosted lightweight Huggingface mirror service that implements mirroring feature for Huggingface resources at file block level, enhancing download speeds and saving bandwidth. It offers cache control policies and allows administrators to configure accessible repositories. Users can install Olah with pip or from source, set up the mirror site, and download models and datasets using huggingface-cli. Olah provides additional configurations through a configuration file for basic setup and accessibility restrictions. Future work includes implementing an administrator and user system, OOS backend support, and mirror update schedule task. Olah is released under the MIT License.
airbyte
Airbyte is an open-source data integration platform that makes it easy to move data from any source to any destination. With Airbyte, you can build and manage data pipelines without writing any code. Airbyte provides a library of pre-built connectors that make it easy to connect to popular data sources and destinations. You can also create your own connectors using Airbyte's no-code Connector Builder or low-code CDK. Airbyte is used by data engineers and analysts at companies of all sizes to build and manage their data pipelines.
airbyte-platform
Airbyte is an open-source data integration platform that makes it easy to move data from any source to any destination. With Airbyte, you can build and manage data pipelines without writing any code. Airbyte provides a library of pre-built connectors that make it easy to connect to popular data sources and destinations. You can also create your own connectors using Airbyte's low-code Connector Development Kit (CDK). Airbyte is used by data engineers and analysts at companies of all sizes to move data for a variety of purposes, including data warehousing, data analysis, and machine learning.
lassxToolkit
lassxToolkit is a versatile tool designed for file processing tasks. It allows users to manipulate files and folders based on specified configurations in a strict .json format. The tool supports various AI models for tasks such as image upscaling and denoising. Users can customize settings like input/output paths, error handling, file selection, and plugin integration. lassxToolkit provides detailed instructions on configuration options, default values, and model selection. It also offers features like tree restoration, recursive processing, and regex-based file filtering. The tool is suitable for users looking to automate file processing tasks with AI capabilities.
gemini-ai
Gemini AI is a Ruby Gem designed to provide low-level access to Google's generative AI services through Vertex AI, Generative Language API, or AI Studio. It allows users to interact with Gemini to build abstractions on top of it. The Gem provides functionalities for tasks such as generating content, embeddings, predictions, and more. It supports streaming capabilities, server-sent events, safety settings, system instructions, JSON format responses, and tools (functions) calling. The Gem also includes error handling, development setup, publishing to RubyGems, updating the README, and references to resources for further learning.
llm-interface
LLM Interface is an npm module that streamlines interactions with various Large Language Model (LLM) providers in Node.js applications. It offers a unified interface for switching between providers and models, supporting 36 providers and hundreds of models. Features include chat completion, streaming, error handling, extensibility, response caching, retries, JSON output, and repair. The package relies on npm packages like axios, @google/generative-ai, dotenv, jsonrepair, and loglevel. Installation is done via npm, and usage involves sending prompts to LLM providers. Tests can be run using npm test. Contributions are welcome under the MIT License.
partial-json-parser-js
Partial JSON Parser is a lightweight and customizable library for parsing partial JSON strings. It allows users to parse incomplete JSON data and stream it to the user. The library provides options to specify what types of partialness are allowed during parsing, such as strings, objects, arrays, special values, and more. It helps handle malformed JSON and returns the parsed JavaScript value. Partial JSON Parser is implemented purely in JavaScript and offers both commonjs and esm builds.
For similar jobs
lollms-webui
LoLLMs WebUI (Lord of Large Language Multimodal Systems: One tool to rule them all) is a user-friendly interface to access and utilize various LLM (Large Language Models) and other AI models for a wide range of tasks. With over 500 AI expert conditionings across diverse domains and more than 2500 fine tuned models over multiple domains, LoLLMs WebUI provides an immediate resource for any problem, from car repair to coding assistance, legal matters, medical diagnosis, entertainment, and more. The easy-to-use UI with light and dark mode options, integration with GitHub repository, support for different personalities, and features like thumb up/down rating, copy, edit, and remove messages, local database storage, search, export, and delete multiple discussions, make LoLLMs WebUI a powerful and versatile tool.
Azure-Analytics-and-AI-Engagement
The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.
minio
MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads.
mage-ai
Mage is an open-source data pipeline tool for transforming and integrating data. It offers an easy developer experience, engineering best practices built-in, and data as a first-class citizen. Mage makes it easy to build, preview, and launch data pipelines, and provides observability and scaling capabilities. It supports data integrations, streaming pipelines, and dbt integration.
AiTreasureBox
AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.
tidb
TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.
airbyte
Airbyte is an open-source data integration platform that makes it easy to move data from any source to any destination. With Airbyte, you can build and manage data pipelines without writing any code. Airbyte provides a library of pre-built connectors that make it easy to connect to popular data sources and destinations. You can also create your own connectors using Airbyte's no-code Connector Builder or low-code CDK. Airbyte is used by data engineers and analysts at companies of all sizes to build and manage their data pipelines.
labelbox-python
Labelbox is a data-centric AI platform for enterprises to develop, optimize, and use AI to solve problems and power new products and services. Enterprises use Labelbox to curate data, generate high-quality human feedback data for computer vision and LLMs, evaluate model performance, and automate tasks by combining AI and human-centric workflows. The academic & research community uses Labelbox for cutting-edge AI research.

