Search Results for "sql performance monitor"
Sort By:
Showing 34 open source projects for "sql performance monitor"
View related business solutions-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
1
Chat2DB
AI-driven database tool and SQL client
Save time by working with data. Connect to all your data sources, and instantly generate optimal SQL for fast lightning information. If you don't know SQL well, you can get instant information without writing SQL. Generate high-performance SQL for your complicated queries using natural language, as well as correcting errors and getting AI suggestions to optimize the performance of SQL queries. Developers can write complex SQL queries quickly and accurately with the help of the AI SQL editor, saving time and improving development efficiency. ... -
2
Arize Phoenix
Uncover insights, surface problems, monitor, and fine tune your LLM
Phoenix provides ML insights at lightning speed with zero-config observability for model drift, performance, and data quality. Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. -
3
NVIDIA NeMo Agent Toolkit
Library for efficiently connecting and optimizing teams of AI agents
NVIDIA NeMo Agent Toolkit is an open-source framework designed to build, optimize, and manage AI agents across different development ecosystems. It provides enterprise-grade tools for improving agent performance, reliability, and observability throughout the development lifecycle. The toolkit integrates with popular agent frameworks such as LangChain, LlamaIndex, CrewAI, Microsoft Semantic Kernel, and Google ADK. Developers can monitor agent execution, trace workflows, and analyze token-level performance to identify bottlenecks and improve efficiency. ... -
4
MyScaleDB
A @ClickHouse fork that supports high-performance vector search
...MyScaleDB enables developers to perform vector similarity searches using standard SQL syntax, eliminating the need to learn specialized vector database query languages. The database is optimized for high performance and scalability, allowing it to handle extremely large datasets and high query loads typical of production AI applications. -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
5
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. -
6
Memobase
Fast backend for long-term AI user memory via structured profiles
...Instead of relying purely on traditional embedding-based retrieval or RAG systems, Memobase uses profile and timeline structures to deliver memory that reflects user context efficiently and meaningfully. 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. -
7
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. ... -
8
Open Gauss
Project-scoped Lean workflow orchestrator from Math, Inc.
Open Gauss is an enterprise-grade open-source relational database management system designed to handle large-scale data processing with high performance, reliability, and security. 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. ... -
9
MCP Server MySQL
A Model Context Protocol server
A Model Context Protocol server that provides access to MySQL databases, enabling Large Language Models to inspect database schemas and execute SQL queries, facilitating seamless database interactions. -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
10
SwanLab
An open-source, modern-design AI training tracking and visualization
SwanLab is an open-source experiment tracking and visualization platform designed to help machine learning engineers monitor, compare, and analyze the training of artificial intelligence models. The tool records training metrics, hyperparameters, model outputs, and experiment configurations so that developers can easily understand how different experiments perform over time. It provides a modern user interface for visualizing results, enabling teams to compare runs, track model performance trends, and collaborate on machine learning research. ... -
11
Sail
A drop-in Apache Spark replacement written in Rust
Sail is an open-source distributed computation framework designed to unify batch processing, stream processing, and AI workloads into a single, high-performance engine. It is built entirely in Rust, eliminating JVM overhead and enabling predictable performance, fast startup times, and improved memory safety compared to traditional big data frameworks. Sail is compatible with the Spark Connect protocol, which means existing Spark SQL and DataFrame workloads can run without code changes, making adoption seamless for teams already using Spark-based pipelines. ... -
12
GPU Hot
Real-time NVIDIA GPU dashboard
GPU Hot is an open-source, lightweight monitoring dashboard designed to provide real-time visibility into NVIDIA GPU performance across single machines or entire clusters. The project offers a self-hosted web interface that streams hardware metrics directly from GPU servers, enabling developers, ML engineers, and system administrators to observe GPU utilization and system behavior in real time through a browser. The dashboard collects and displays a wide range of performance metrics... -
13
Tiledesk Dashboard
Tiledesk is the open source AI agent builder
Tiledesk Dashboard is the frontend management interface for the Tiledesk platform, allowing administrators to configure settings, monitor live chats, and manage chatbot workflows. -
14
Agent Behavior Monitoring
The open source post-building layer for agents
Agent Behavior Monitoring is an open-source framework designed to monitor, evaluate, and improve the behavior of AI agents operating in real or simulated environments. The system focuses on agent behavior monitoring by collecting interaction data and analyzing how agents perform across different scenarios and tasks. Developers can use the framework to observe agent actions in both online production environments and offline evaluation settings, making it useful for debugging and performance analysis. ... -
15
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. -
16
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. -
17
ChatLab
Local-first AI chat analysis tool for insights from conversation data
ChatLab is an open source desktop application designed to help users analyze and better understand their personal chat histories through structured data exploration and AI-assisted insights. It enables users to import chat exports from multiple messaging platforms and transform them into a unified data model for consistent analysis. By combining a flexible SQL engine with AI agents, the tool allows users to query, summarize, and explore conversation patterns in a more interactive and... -
18
LlamaIndex
Central interface to connect your LLM's with external data
LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data. LlamaIndex is a simple, flexible interface between your external data and LLMs. It provides the following tools in an easy-to-use fashion. Provides indices over your unstructured and structured data for use with LLM's. These indices help to abstract away common boilerplate and pain points for in-context learning. Dealing with prompt limitations (e.g. 4096 tokens for Davinci) when... -
19
LangWatch
The platform for LLM evaluations and AI agent testing
LangWatch is an open-source observability and monitoring platform designed to help developers evaluate and improve applications built with large language models. The platform provides tools for tracking model interactions, analyzing prompt behavior, and identifying issues such as hallucinations, latency problems, or unexpected responses. By collecting telemetry data from AI applications, LangWatch allows developers to understand how their systems perform in real-world usage scenarios. The... -
20
Korvus
Korvus is a search SDK that unifies the entire RAG pipeline
Korvus is an open-source retrieval-augmented generation (RAG) pipeline designed to run entirely inside PostgreSQL, allowing developers to build AI search and knowledge systems directly within a database environment. The project consolidates the typical steps of a RAG pipeline—including embedding generation, document retrieval, reranking, and text generation—into a single query executed within the Postgres ecosystem. By leveraging PostgresML and vector extensions such as pgvector, Korvus... -
21
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... -
22
OpenClaw Office
OpenClaw Office is the visual monitoring and management frontend
...The platform enables real-time visualization of agent states, interactions, and workflows, making complex multi-agent coordination easier to understand and debug. Users can observe communication flows between agents through visual connections, track token usage and operational costs, and analyze performance through integrated dashboards and charts. The system also includes live chat capabilities, allowing users to monitor conversations and tool calls as they occur. -
23
MCP Toolbox for Databases
Open source MCP server that exposes database tools for AI agents
...It also supports observability through built-in metrics and tracing capabilities, allowing developers to monitor how tools are used and debug interactions. -
24
ClawPort
Open-source AI agent command center for Claude Code agent teams
ClawPort is an open-source web-based dashboard designed to act as a centralized command center for managing and interacting with OpenClaw AI agent systems. It provides a visual interface that replaces fragmented terminal-based workflows, allowing users to monitor, control, and communicate with multiple agents from a single location. The platform is built to improve visibility into multi-agent environments, offering insights into agent activity, task execution, and system performance in real time. It supports direct interaction with agents through chat interfaces, enabling users to guide or override automated workflows when necessary. ... -
25
Acontext
Context data platform for building observable, self-learning AI agents
...Acontext also supports agent self-learning by distilling structured skills and experiences from previously completed tasks, which can later be reused or searched to improve future performance. It includes tools to interact with session data, background agents that monitor progress, and a dashboard that visualizes success rates, artifacts, and learned skills. By combining persistent storage, observability, and learning capabilities, Acontext aims to make AI agents more scalable, reliable, and capable.