Best AI tools for< Improve Database Performance >

EverSQL is an AI-powered SQL query optimizer and database observability tool that specializes in optimizing PostgreSQL and MySQL databases. It offers automatic SQL query optimization, ongoing performance insights, and cost reduction recommendations. With over 100,000 professionals trusting EverSQL, it aims to save time and improve database performance by making SQL queries faster and more efficient.

Nabubit is an AI-powered tool designed to assist users in database design. It serves as a virtual copilot, providing guidance and suggestions throughout the database design process. With Nabubit, users can streamline their database creation, optimize performance, and ensure data integrity. The tool leverages artificial intelligence to analyze data requirements, suggest schema designs, and enhance overall database efficiency. Nabubit is a valuable resource for developers, data analysts, and businesses looking to improve their database management practices.

Ylopo is an AI-driven lead generation, follow-up, and database management platform designed for real estate agents and teams. It offers a suite of AI-powered tools and features to help users generate high-quality seller leads, nurture leads, and improve lead conversion rates. Ylopo's AI technology is integrated into various aspects of the platform to enhance performance and efficiency. The platform also provides training courses, CRM integration, dynamic video ads, and mission control dashboard for users to manage their marketing campaigns effectively.

AlphaRank is an AI SEO optimizer tool designed to boost website traffic by providing advanced SEO solutions. It offers a comprehensive suite of features to audit and optimize websites, leveraging AI algorithms and a vast database of keywords and merchant insights. Trusted by top-tier partners, AlphaRank aims to enhance content relevance, user engagement, and SEO precision for businesses, bloggers, and freelancers. The tool streamlines SEO operations, provides market insights, and offers expert recommendations for technical and content improvements.

Weaviate is an AI-native database designed to bring intuitive AI-native applications to life with less hallucination, data leakage, and vendor lock-in. It offers features like Hybrid Search, Retrieval-Augmented Generation, Generative Feedback Loops, and Cost-performance optimization. Weaviate empowers developers to build AI-native applications with flexible, reliable, open-source foundations, including a vector database and surrounding services. With over 1M monthly downloads, Weaviate is a core piece of the AI-native stack for developers and enterprises, providing model inference and AI infrastructure tailored to specific use cases.

Respaid is a B2B collections tool that focuses on respectful and efficient debt recovery. It utilizes AI-powered precision messaging to optimize communication with debtors, resulting in a 50% collection rate and 30x faster performance than traditional methods. The tool offers features such as direct payments, database cleaning, and insights into why customers aren't paying. Respaid aims to protect your brand reputation while helping you recover unpaid invoices in a respectful manner.

LogicMonitor is a cloud-based infrastructure monitoring platform that provides real-time insights and automation for comprehensive, seamless monitoring with agentless architecture. It offers a wide range of features including infrastructure monitoring, network monitoring, server monitoring, remote monitoring, virtual machine monitoring, SD-WAN monitoring, database monitoring, storage monitoring, configuration monitoring, cloud monitoring, container monitoring, AWS Monitoring, GCP Monitoring, Azure Monitoring, digital experience SaaS monitoring, website monitoring, APM, AIOPS, Dexda Integrations, security dashboards, and platform demo logs. LogicMonitor's AI-driven hybrid observability helps organizations simplify complex IT ecosystems, accelerate incident response, and thrive in the digital landscape.

Langtrace AI is an open-source observability tool powered by Scale3 Labs that helps monitor, evaluate, and improve LLM (Large Language Model) applications. It collects and analyzes traces and metrics to provide insights into the ML pipeline, ensuring security through SOC 2 Type II certification. Langtrace supports popular LLMs, frameworks, and vector databases, offering end-to-end observability and the ability to build and deploy AI applications with confidence.

AI2SQL is an AI-powered SQL query builder and generator that allows users to create, optimize, and automate SQL queries without the need for expert skills. The tool transforms natural language instructions into precise SQL and NoSQL queries, simplifying database design and enhancing query performance. With features like Text2SQL, SQL Query Fixer, SQL Query Explainer, and SQL Query Optimizer, AI2SQL offers a streamlined solution for diverse SQL tasks. Trusted by industry leaders, AI2SQL saves time, reduces errors, and improves productivity for data analysts and developers.

DB Sensei is an AI-powered SQL tool that helps developers generate, fix, explain, and format SQL queries with ease. It features a user-friendly interface, AI-driven query generation, query fixing, query explaining, and query formatting. DB Sensei is designed for developers, database administrators, and students who want to get faster results and improve their database skills.

GoSearch is an AI-powered Enterprise Search and Resource Discovery platform that enables users to search all internal apps and resources in seconds with the help of AI technology. It offers features like AI workplace assistant, unified knowledge hub, multimodal AI, custom GPTs, and a no-code AI chatbot builder. GoSearch aims to streamline knowledge management and boost productivity by providing instant answers and information discovery through advanced search innovations.

Snaplet is a data management tool for developers that provides AI-generated dummy data for local development, end-to-end testing, and debugging. It uses a real programming language (TypeScript) to define and edit data, ensuring type safety and auto-completion. Snaplet understands database structures and relationships, automatically transforming personally identifiable information and seeding data accordingly. It integrates seamlessly into development workflows, providing data where it's needed most: on local machines, for CI/CD testing, and preview environments.

Likely.AI is an AI-powered platform designed for the real estate industry, offering innovative solutions to enhance database management, marketing content creation, and predictive analytics. The platform utilizes advanced AI models to predict likely sellers, update contact information, and trigger automated notifications, ensuring real estate professionals stay ahead of the competition. With features like contact enrichment, predictive modeling, 24/7 contact monitoring, and AI-driven marketing content generation, Likely.AI revolutionizes how real estate businesses operate and engage with their clients. The platform aims to streamline workflows, improve lead generation, and maximize ROI for users in the residential real estate sector.

GPTSHunter is an AI-powered tool that leverages advanced natural language processing to generate human-like text based on the input provided. The tool is designed to assist users in creating content, generating ideas, and improving writing efficiency. By utilizing cutting-edge AI technology, GPTSHunter aims to streamline the content creation process and enhance user productivity.

Coginiti is a collaborative analytics platform and tools designed for SQL developers, data scientists, engineers, and analysts. It offers capabilities such as AI assistant, data mesh, database & object store support, powerful query & analysis, and share & reuse curated assets. Coginiti empowers teams and organizations to manage collaborative practices, data efficiency, and deliver trusted data products faster. The platform integrates modular analytic development, collaborative versioned teamwork, and a data quality framework to enhance productivity and ensure data reliability. Coginiti also provides an AI-enabled virtual analytics advisor to boost team efficiency and empower data heroes.

ProspectEdge is an AI-powered sales tool designed for B2B teams. It provides valuable insights and data-driven recommendations to enhance sales strategies and improve customer engagement. By leveraging artificial intelligence, ProspectEdge helps businesses identify potential leads, understand customer behavior, and optimize sales processes. With its advanced algorithms and predictive analytics, the tool empowers sales professionals to make informed decisions and drive revenue growth.

AIExh is a platform dedicated to discovering and following the hottest open-source AI projects. It serves as the #1 database for open-source AI, providing daily updates and recommendations. With a user base of over 1000 humans and 1000+ subscribers, AIExh covers a wide range of AI applications such as image identification, speech recognition, machine translation, and more. Users can explore various AI projects, submit their own projects, and stay updated on the latest advancements in artificial intelligence.

Coefficient is a data connector tool for Google Sheets and Excel that empowers users to unlock the full potential of their spreadsheets by providing live connections to over 60 business systems. It offers features such as two-way syncing, automatic refreshes, and scheduled alerts, all powered by AI. Coefficient streamlines data import, visualization, and system updates, enabling users to eliminate manual work, improve data accuracy, and save time. Trusted by over 50,000 companies, Coefficient is a user-friendly tool that enhances data analysis and reporting processes.

Text2SQL.AI is an AI-powered SQL query builder that helps users generate optimized SQL queries effortlessly. It supports various AI-powered services, including SQL query building from textual instructions, SQL query explanation to plain English, SQL query error fixation, adding custom database schemas, SQL dialects for various database types, Microsoft Excel and Google Sheets formula generation and explanation, and Regex expression generation and explanation. The tool is designed to improve SQL skills, save time, and assist beginners, data analysts, data scientists, data engineers, and software developers in their work.

AIndLeads is an AI-powered B2B tool that combines a database, CRM, and lead generation capabilities. It leverages artificial intelligence to provide businesses with valuable insights and streamline their sales and marketing processes. With AIndLeads, users can access accurate and up-to-date B2B data, manage customer relationships efficiently, and generate high-quality leads to drive business growth.

Laravel Slower is a powerful package designed for Laravel developers to optimize the performance of their applications by identifying slow database queries and providing AI-driven suggestions for optimal indexing strategies and performance improvements. It offers actionable insights for debugging and monitoring database interactions, enhancing efficiency and scalability.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

Codefuse-ModelCache is a semantic cache for large language models (LLMs) that aims to optimize services by introducing a caching mechanism. It helps reduce the cost of inference deployment, improve model performance and efficiency, and provide scalable services for large models. The project caches pre-generated model results to reduce response time for similar requests and enhance user experience. It integrates various embedding frameworks and local storage options, offering functionalities like cache-writing, cache-querying, and cache-clearing through RESTful API. The tool supports multi-tenancy, system commands, and multi-turn dialogue, with features for data isolation, database management, and model loading schemes. Future developments include data isolation based on hyperparameters, enhanced system prompt partitioning storage, and more versatile embedding models and similarity evaluation algorithms.

Lantern is an open-source PostgreSQL database extension designed to store vector data, generate embeddings, and handle vector search operations efficiently. It introduces a new index type called 'lantern_hnsw' for vector columns, which speeds up 'ORDER BY ... LIMIT' queries. Lantern utilizes the state-of-the-art HNSW implementation called usearch. Users can easily install Lantern using Docker, Homebrew, or precompiled binaries. The tool supports various distance functions, index construction parameters, and operator classes for efficient querying. Lantern offers features like embedding generation, interoperability with pgvector, parallel index creation, and external index graph generation. It aims to provide superior performance metrics compared to other similar tools and has a roadmap for future enhancements such as cloud-hosted version, hardware-accelerated distance metrics, industry-specific application templates, and support for version control and A/B testing of embeddings.

chromem-go is an embeddable vector database for Go with a Chroma-like interface and zero third-party dependencies. It enables retrieval augmented generation (RAG) and similar embeddings-based features in Go apps without the need for a separate database. The focus is on simplicity and performance for common use cases, allowing querying of documents with minimal memory allocations. The project is in beta and may introduce breaking changes before v1.0.0.

Greenplum Database (GPDB) is an advanced, fully featured, open source data warehouse, based on PostgreSQL. It provides powerful and rapid analytics on petabyte scale data volumes. Uniquely geared toward big data analytics, Greenplum Database is powered by the world’s most advanced cost-based query optimizer delivering high analytical query performance on large data volumes.

Züs is a high-performance cloud on a fast blockchain offering privacy and configurable uptime. It uses erasure code to distribute data between data and parity servers, allowing flexibility for IT managers to design for security and uptime. Users can easily share encrypted data with business partners through a proxy key sharing protocol. The ecosystem includes apps like Blimp for cloud migration, Vult for personal cloud storage, and Chalk for NFT artists. Other apps include Bolt for secure wallet and staking, Atlus for blockchain explorer, and Chimney for network participation. The QoS protocol challenges providers based on response time, while the privacy protocol enables secure data sharing. Züs supports hybrid and multi-cloud architectures, allowing users to improve regulatory compliance and security requirements.

This repository contains the code for LongRAG, a framework that enhances retrieval-augmented generation with long-context LLMs. LongRAG introduces a 'long retriever' and a 'long reader' to improve performance by using a 4K-token retrieval unit, offering insights into combining RAG with long-context LLMs. The repo provides instructions for installation, quick start, corpus preparation, long retriever, and long reader.

Codefuse-ModelCache is a semantic cache for large language models (LLMs) that aims to optimize services by introducing a caching mechanism. It helps reduce the cost of inference deployment, improve model performance and efficiency, and provide scalable services for large models. The project facilitates sharing and exchanging technologies related to large model semantic cache through open-source collaboration.

Superlinked is a compute framework for information retrieval and feature engineering systems, focusing on converting complex data into vector embeddings for RAG, Search, RecSys, and Analytics stack integration. It enables custom model performance in machine learning with pre-trained model convenience. The tool allows users to build multimodal vectors, define weights at query time, and avoid postprocessing & rerank requirements. Users can explore the computational model through simple scripts and python notebooks, with a future release planned for production usage with built-in data infra and vector database integrations.

Floneum is a graph editor that makes it easy to develop your own AI workflows. It uses large language models (LLMs) to run AI models locally, without any external dependencies or even a GPU. This makes it easy to use LLMs with your own data, without worrying about privacy. Floneum also has a plugin system that allows you to improve the performance of LLMs and make them work better for your specific use case. Plugins can be used in any language that supports web assembly, and they can control the output of LLMs with a process similar to JSONformer or guidance.

h2oGPT is an Apache V2 open-source project that allows users to query and summarize documents or chat with local private GPT LLMs. It features a private offline database of any documents (PDFs, Excel, Word, Images, Video Frames, Youtube, Audio, Code, Text, MarkDown, etc.), a persistent database (Chroma, Weaviate, or in-memory FAISS) using accurate embeddings (instructor-large, all-MiniLM-L6-v2, etc.), and efficient use of context using instruct-tuned LLMs (no need for LangChain's few-shot approach). h2oGPT also offers parallel summarization and extraction, reaching an output of 80 tokens per second with the 13B LLaMa2 model, HYDE (Hypothetical Document Embeddings) for enhanced retrieval based upon LLM responses, a variety of models supported (LLaMa2, Mistral, Falcon, Vicuna, WizardLM. With AutoGPTQ, 4-bit/8-bit, LORA, etc.), GPU support from HF and LLaMa.cpp GGML models, and CPU support using HF, LLaMa.cpp, and GPT4ALL models. Additionally, h2oGPT provides Attention Sinks for arbitrarily long generation (LLaMa-2, Mistral, MPT, Pythia, Falcon, etc.), a UI or CLI with streaming of all models, the ability to upload and view documents through the UI (control multiple collaborative or personal collections), Vision Models LLaVa, Claude-3, Gemini-Pro-Vision, GPT-4-Vision, Image Generation Stable Diffusion (sdxl-turbo, sdxl) and PlaygroundAI (playv2), Voice STT using Whisper with streaming audio conversion, Voice TTS using MIT-Licensed Microsoft Speech T5 with multiple voices and Streaming audio conversion, Voice TTS using MPL2-Licensed TTS including Voice Cloning and Streaming audio conversion, AI Assistant Voice Control Mode for hands-free control of h2oGPT chat, Bake-off UI mode against many models at the same time, Easy Download of model artifacts and control over models like LLaMa.cpp through the UI, Authentication in the UI by user/password via Native or Google OAuth, State Preservation in the UI by user/password, Linux, Docker, macOS, and Windows support, Easy Windows Installer for Windows 10 64-bit (CPU/CUDA), Easy macOS Installer for macOS (CPU/M1/M2), Inference Servers support (oLLaMa, HF TGI server, vLLM, Gradio, ExLLaMa, Replicate, OpenAI, Azure OpenAI, Anthropic), OpenAI-compliant, Server Proxy API (h2oGPT acts as drop-in-replacement to OpenAI server), Python client API (to talk to Gradio server), JSON Mode with any model via code block extraction. Also supports MistralAI JSON mode, Claude-3 via function calling with strict Schema, OpenAI via JSON mode, and vLLM via guided_json with strict Schema, Web-Search integration with Chat and Document Q/A, Agents for Search, Document Q/A, Python Code, CSV frames (Experimental, best with OpenAI currently), Evaluate performance using reward models, and Quality maintained with over 1000 unit and integration tests taking over 4 GPU-hours.

Cosdata is a cutting-edge AI data platform designed to power the next generation search pipelines. It features immutability, version control, and excels in semantic search, structured knowledge graphs, hybrid search capabilities, real-time search at scale, and ML pipeline integration. The platform is customizable, scalable, efficient, enterprise-grade, easy to use, and can manage multi-modal data. It offers high performance, indexing, low latency, and high requests per second. Cosdata is designed to meet the demands of modern search applications, empowering businesses to harness the full potential of their data.

This repository focuses on utilizing generative AI to bridge the gap between natural language questions and SQL queries, aiming to improve data consumption in enterprise data warehouses. It addresses challenges in SQL query generation, such as foreign key relationships and table joins, and highlights the importance of accuracy metrics like Execution Accuracy (EX) and Exact Set Match Accuracy (EM). The workshop content covers advanced prompt engineering, Retrieval Augmented Generation (RAG), fine-tuning models, and security measures against prompt and SQL injections.

Bee is an easy and high efficiency ORM framework that simplifies database operations by providing a simple interface and eliminating the need to write separate DAO code. It supports various features such as automatic filtering of properties, partial field queries, native statement pagination, JSON format results, sharding, multiple database support, and more. Bee also offers powerful functionalities like dynamic query conditions, transactions, complex queries, MongoDB ORM, cache management, and additional tools for generating distributed primary keys, reading Excel files, and more. The newest versions introduce enhancements like placeholder precompilation, default date sharding, ElasticSearch ORM support, and improved query capabilities.

Awesome LLM for APR is a repository dedicated to exploring the capabilities of Large Language Models (LLMs) in Automated Program Repair (APR). It provides a comprehensive collection of research papers, tools, and resources related to using LLMs for various scenarios such as repairing semantic bugs, security vulnerabilities, syntax errors, programming problems, static warnings, self-debugging, type errors, web UI tests, smart contracts, hardware bugs, performance bugs, API misuses, crash bugs, test case repairs, formal proofs, GitHub issues, code reviews, motion planners, human studies, and patch correctness assessments. The repository serves as a valuable reference for researchers and practitioners interested in leveraging LLMs for automated program repair.

Ragas is a framework that helps you evaluate your Retrieval Augmented Generation (RAG) pipelines. RAG denotes a class of LLM applications that use external data to augment the LLM’s context. There are existing tools and frameworks that help you build these pipelines but evaluating it and quantifying your pipeline performance can be hard. This is where Ragas (RAG Assessment) comes in. Ragas provides you with the tools based on the latest research for evaluating LLM-generated text to give you insights about your RAG pipeline. Ragas can be integrated with your CI/CD to provide continuous checks to ensure performance.

DB-GPT-Hub is an experimental project leveraging Large Language Models (LLMs) for Text-to-SQL parsing. It includes stages like data collection, preprocessing, model selection, construction, and fine-tuning of model weights. The project aims to enhance Text-to-SQL capabilities, reduce model training costs, and enable developers to contribute to improving Text-to-SQL accuracy. The ultimate goal is to achieve automated question-answering based on databases, allowing users to execute complex database queries using natural language descriptions. The project has successfully integrated multiple large models and established a comprehensive workflow for data processing, SFT model training, prediction output, and evaluation.

Nucleoid is a declarative (logic) runtime environment that manages both data and logic under the same runtime. It uses a declarative programming paradigm, which allows developers to focus on the business logic of the application, while the runtime manages the technical details. This allows for faster development and reduces the amount of code that needs to be written. Additionally, the sharding feature can help to distribute the load across multiple instances, which can further improve the performance of the system.

Assists in optimizing SQL code with best practices and efficiency tips.

Create the most effective database or search engine queries using keywords, truncation, and Boolean operators!

Expert in brief, direct SQL queries for BigQuery, with casual professional tone.

Tech-savvy manager for computer-based problem-solving.

Project guidance with in-depth tech education

Assists with tech exam prep, adheres to specific rules.

Assists in coding .NET ecommerce API and dashboard using SQL and Entity Framework.

WRC 번역 데이터베이스 참조, 정확도 주의.

Gives you tips and suggestions on how you can improve your application for your users.

Upload a screenshot of your Tinder profile to improve it and get feedback

Improve your Ideas with First Principles Thinking

Offers exercises and techniques to improve memory retention and cognitive functions.

Generates conversation examples and chunks for specified situations. Improve your instantaneous conversational skills through repetitive practice!

Improve your physical & mental health

Analyzes customer churn and provides strategies to improve loyalty and retention.

Improve your curriculum telling chatgpt your cv and the desired job

Agile expert providing practical, step-by-step advice with the agile way of working of your team and organisation. Whether you're looking to improve your Agile skills or find solutions to specific problems. Including Scrum, Kanban and SAFe knowledge.

I improve objects with animals.

I improve marketing effectiveness by designing stunning research-led assets in a flash!

Helps improve language skills through interactive scenarios and feedback.