Search Results for "sql" - Page 2
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Showing 143 open source projects for "sql"
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Top Corporate LMS for Training | Best Learning Management SoftwareAxis LMS enables you to deliver online and virtual learning and training through a scalable, easy-to-use LMS that is designed to enhance your training, automate your workflows, engage your learners and keep you compliant.
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Junie, the AI coding agent by JetBrainsJunie is an AI-powered coding agent developed by JetBrains designed to enhance developer productivity by integrating directly into popular IDEs such as IntelliJ IDEA, PyCharm, and Android Studio. It supports developers by assisting with code completion, testing, and inspections, ensuring code quality and reducing debugging time.
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Memobase
Fast backend for long-term AI user memory via structured profiles
...The system focuses on three principal performance metrics: high search performance, reduced large language model (LLM) costs through batch processing techniques, and low latency with minimal SQL operations. Memobase supports integration with existing LLM workflows via APIs and SDKs (including Python, Node, and Go), making it easy to adopt within diverse application stacks. -
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pgai
A suite of tools to develop RAG, semantic search, and other AI apps
...It integrates tools for vector storage, advanced indexing, and AI model interactions, facilitating the development of applications like semantic search and Retrieval-Augmented Generation (RAG) without leaving the SQL environment. -
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DB MCP Server
A powerful multi-database server implementing the MCP
The DB MCP Server is a powerful multi-database server implementing the Model Context Protocol (MCP) to provide AI assistants with structured access to databases. Built on the FreePeak/cortex framework, it enables execution of SQL queries, transaction management, schema exploration, and performance analysis across different database systems through a unified interface. -
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SAG
SQL-Driven RAG Engine
SAG is an open-source SQL-driven retrieval-augmented generation engine that dynamically constructs knowledge graphs during query processing. Instead of relying on a static knowledge graph prepared in advance, the system automatically builds relational structures between entities while processing user queries. Documents are first decomposed into atomic semantic events, which are then represented using multidimensional natural language vectors. -
All-in-one solution to control corporate spendingWallester Business is a leading world-class solution to optimize your company’s financial processes! Issuing virtual and physical corporate expense cards with an IBAN account, expense monitoring, limit regulation, convenient accounting, subscription control — manage your finance on all-in-one platform in real time! Wallester Business benefits your business growth!
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Liger Kernel
Efficient Triton Kernels for LLM Training
Liger Kernel is a unified kernel developed by LinkedIn to streamline data science and machine learning workflows across different languages and tools. It provides a consistent interface for running code in various languages (such as Python, R, SQL) within a single Jupyter-like environment, enhancing productivity and collaboration for data scientists working in mixed-language projects. -
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Haystack
Haystack is an open source NLP framework to interact with your data
...Pick any Transformer model from Hugging Face's Model Hub, experiment, find the one that works. Use Haystack NLP components on top of Elasticsearch, OpenSearch, or plain SQL. Boost search performance with Pinecone, Milvus, FAISS, or Weaviate vector databases, and dense passage retrieval. -
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Spice.ai OSS
A self-hostable CDN for databases
...Spice makes it easy and fast to query data from one or more sources using SQL. You can co-locate a managed dataset with your application or machine learning model, and accelerate it with Arrow in-memory, SQLite/DuckDB, or with attached PostgreSQL for fast, high-concurrency, low-latency queries. Accelerated engines give you flexibility and control over query cost and performance. -
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DB-GPT
Revolutionizing Database Interactions with Private LLM Technology
DB-GPT is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure. -
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Open Gauss
Project-scoped Lean workflow orchestrator from Math, Inc.
...It is based on the PostgreSQL ecosystem but significantly extends its capabilities through architectural optimizations, AI-driven features, and enterprise-level enhancements. The database organizes data using the relational model, storing structured information in tables composed of rows and columns while supporting standard SQL for querying and management. One of its defining strengths is its optimization for multi-core and distributed environments, allowing it to efficiently process high volumes of concurrent transactions with minimal latency. OpenGauss also incorporates AI-based optimization techniques, such as intelligent query planning, performance prediction, and automated tuning, which help reduce operational complexity and improve efficiency. -
Securely stream and govern industrial data to power intelligent operations with agentic insights.Trusted MQTT Platform — Fully-managed and cloud-native MQTT platform for bi-directional IoT data movement.
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MindsDB
Making Enterprise Data Intelligent and Responsive for AI
MindsDB is an AI data solution that enables humans, AI, agents, and applications to query data in natural language and SQL, and get highly accurate answers across disparate data sources and types. MindsDB connects to diverse data sources and applications, and unifies petabyte-scale structured and unstructured data. Powered by an industry-first cognitive engine that can operate anywhere (on-prem, VPC, serverless), it empowers both humans and AI with highly informed decision-making capabilities. ... -
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Deepnote
Deepnote is a drop-in replacement for Jupyter
...Built on top of the Jupyter kernel ecosystem, it maintains compatibility with existing notebook workflows while introducing additional features focused on collaboration and automation. The system supports programming languages such as Python, R, and SQL and allows users to execute and analyze data directly within interactive notebooks. Deepnote emphasizes team-based data science by enabling real-time collaboration similar to shared document editors, allowing multiple users to work simultaneously on the same notebook environment. -
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Data-Science-Interview-Questions-Answers
Curated list of data science interview questions and answers
...The repository focuses on core data science fundamentals rather than acting as a software framework, which makes it especially useful as a study and revision resource. Its content is organized into subject-specific documents that cover machine learning, deep learning, statistics, probability, Python, SQL and databases, and resume-based interview questions. That structure makes it practical for users who want to study by topic, strengthen weak areas, or simulate the range of questions they may encounter in interviews. -
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Data Science Interviews
Data science interview questions and answers
...Many of the questions cover fundamental machine learning topics such as linear models, decision trees, neural networks, and evaluation metrics. In addition to theoretical questions, the repository also includes practical interview topics related to coding challenges, SQL queries, and algorithmic thinking. -
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DBHub
Universal database MCP server connecting to MySQL, PostgreSQL
...It supports multiple transports—stdio for desktop clients and HTTP for networked scenarios—making it flexible to embed or deploy. Configuration is environment-variable driven, with a DSN and per-engine settings covering Postgres, MySQL, MariaDB, SQL Server, and SQLite. Operational flags include read-only mode, row limits, and even SSH tunneling options for secure access into private networks. A demo mode ships with an in-memory SQLite “employee” dataset so users can try the tools immediately without provisioning a database. The project lives in the Bytebase org alongside database DevSecOps tooling, underscoring a production focus on safe and auditable DB interaction. -
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MemMachine
Universal memory layer for AI Agents
...Unlike ephemeral LLM prompt state, MemMachine supports distinct memory types—short-term conversational context, long-term persistent knowledge, and profile memory for personalized facts—persisted in optimized stores (e.g., graph databases for episodic lines of reasoning and SQL for user facts) to support robust, context-aware intelligence in agents. It offers flexible APIs, a Python SDK, REST interfaces, and MCP (Model Context Protocol) connectivity to integrate seamlessly with agent frameworks receiving and storing memories over time, effectively boosting relevance, continuity, and tailored behavior. -
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Databend
Cloud-native open source data warehouse for analytics and AI queries
...This architecture enables cost-efficient storage and elastic scaling for workloads that involve large datasets and complex queries. Databend provides a unified engine capable of handling analytics, vector search, and full-text search within a single platform. Databend supports SQL-based workflows and enables real-time data ingestion, transformation, and analysis through streaming and task orchestration features. With its cloud-native design and distributed architecture, Databend can run both as a self-hosted system or within managed environments to power data analytics, AI workloads, and large-scale data. -
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HeavyDB
HeavyDB (formerly MapD/OmniSciDB)
HeavyDB is an open-source GPU-accelerated analytical database designed to perform extremely fast queries on large datasets. The system is built as a SQL-based relational columnar database engine that leverages modern hardware parallelism, including GPUs and multicore CPUs. Its architecture allows users to query datasets containing billions of rows in milliseconds without requiring traditional indexing, pre-aggregation, or sampling techniques. HeavyDB was originally developed as part of the OmniSci platform (formerly MapD) and is commonly used for large-scale analytics and geospatial data processing. ... -
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Logfire MCP
The Logfire MCP Server is here
The Logfire MCP Server is a Model Context Protocol server that allows AI applications to access OpenTelemetry traces and metrics sent to Logfire. It enables retrieval and analysis of telemetry data, enhancing debugging and observability workflows. -
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1Panel
1Panel provides an intuitive web interface and MCP Server
1Panel is a comprehensive Linux server management dashboard and MCP server built in Go. It offers UI control over websites, containers, databases, file systems, LLMs, backups, and monitoring, streamlining typical admin workflows via web. -
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PostgresML
The GPU-powered AI application database
...Leverage multiple types of natural language processing and machine learning models such as vector search and personalization with embeddings to improve search results. Leverage your data with time series forecasting to garner key business insights. Build statistical and predictive models with the full power of SQL and dozens of regression algorithms. Return results and detect fraud faster with ML at the database layer. PostgresML abstracts the data management overhead from the ML/AI lifecycle by enabling users to run ML/LLM models directly on a Postgres database. -
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MCP Timeplus
Execute SQL queries and manage databases seamlessly with Timeplus
An MCP server designed for integration with Timeplus, enabling real-time data streaming and analytics through natural language interactions. -
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KOM
Kubernetes Operations Manager
A Kubernetes Operations Manager (kom) that serves as an SDK-level tool, encapsulating functionalities of kubectl and client-go, providing a comprehensive suite of features for managing Kubernetes resources efficiently. -
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JimuReport
Open source drag-and-drop reporting and dashboard builder platform
...JimuReport also includes components for building interactive charts, data tables, and analytical displays that can be used in enterprise applications. It can connect to multiple data sources and retrieve data through SQL queries, APIs, or other structured formats. It can be embedded into Java applications using Spring Boot integration modules. -
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Pydantic Logfire
Python observability platform for tracing apps, metrics, and logs
Pydantic Logfire is an observability platform designed to help developers monitor, analyze, and understand the behavior of their applications in real time. It is built by the team behind Pydantic and follows a philosophy of combining powerful capabilities with ease of use, making it accessible to entire engineering teams. Pydantic Logfire provides deep visibility into application performance by capturing traces, metrics, and logs through an OpenTelemetry-based architecture. It is... -
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DataProfiler
Extract schema, statistics and entities from datasets
DataProfiler is an AI-powered tool for automatic data analysis and profiling, designed to detect patterns, anomalies, and schema inconsistencies in structured and unstructured datasets. The DataProfiler is a Python library designed to make data analysis, monitoring, and sensitive data detection easy. Loading Data with a single command, the library automatically formats & loads files into a DataFrame. Profiling the Data, the library identifies the schema, statistics, entities (PII / NPI), and...
