9 Repos
APIs and methods for filtering and querying stored data.
Distinguishing note: No candidates provided; grouping under Data & Databases as it pertains to API querying.
Explore 9 awesome GitHub repositories matching data & databases · Query Interfaces. Refine with filters or upvote what's useful.
This project is a containerized implementation of a blockchain node for the Base network. It manages the execution and consensus processes of an Ethereum Virtual Machine node within an isolated environment to maintain the network and process blockchain data. The infrastructure includes a specialized interface for processing pending blocks via websockets to reduce latency. It also provides a state synchronization tool that uses pre-computed snapshots to accelerate the process of reaching the current block height. The system covers network identity configuration for mainnet and testnet environ
Provides a dedicated interface to query and process blockchain blocks in their pending state.
Payload is a headless content management system and application framework that uses a code-first approach to define data schemas and administrative interfaces. By utilizing a centralized, type-safe configuration object, it automatically generates database schemas, API endpoints, and a fully customizable admin panel. The system is built on a database-agnostic architecture, allowing it to interface with various storage engines while providing a unified, type-safe API for server-side operations, REST, and GraphQL. What distinguishes Payload is its deep extensibility and developer-centric design.
Queries related documents using filters and sorting across multiple API types.
MindsDB is an AI-native database engine that treats machine learning models and autonomous agents as virtual tables. By mapping external data sources, predictive models, and third-party services directly into the database schema, it enables users to perform inference, data retrieval, and complex orchestration using standard SQL syntax. The platform distinguishes itself through an autonomous agent orchestrator that executes iterative reasoning loops, allowing agents to plan data access and synthesize natural language responses from connected knowledge bases. It functions as a federated data ga
Translates standard database queries into API calls and model inference requests to provide a unified interaction layer.
Qdrant is a high-performance vector similarity database designed to store, index, and search high-dimensional vectors alongside structured metadata. It functions as a distributed search engine that manages large-scale data clusters, providing low-latency retrieval and complex filtering capabilities. The system is built to serve as a specialized middleware layer, connecting machine learning pipelines and AI agents to persistent storage for intelligent information retrieval and recommendation tasks. The platform distinguishes itself through advanced retrieval techniques, including support for h
Executes similarity searches and random sampling tasks using a unified interface supporting filtering and pagination.
InfluxDB is a high-performance time-series database designed for collecting, storing, and querying time-stamped metrics and event data. It functions as a columnar time-series store and a real-time analytics engine, providing a network-accessible interface for retrieving and analyzing temporal records. The system utilizes a specialized columnar storage format to support high ingestion rates and efficient data retrieval. It incorporates a programmable runtime for executing custom plugins and triggers, including integration for processing and transforming incoming data streams. The platform cov
Provides a network-accessible interface for retrieving and analyzing time-series records.
🔥 基于大模型和 RAG 的智能问数系统,对话式数据分析神器。Text-to-SQL Generation via LLMs using RAG.
Exposes the query system as an embeddable iframe, popup, or MCP call for integration into external workflow tools.
Flask-SQLAlchemy ist ein Toolkit, das das relationale Datenbank-Toolkit SQLAlchemy mit dem Flask-Web-Framework integriert. Es ermöglicht relationale Datenmodellierung durch die Definition von Datenbanktabellenstrukturen als Python-Klassen und verwaltet die Persistenz und den Abruf von Datenbankdatensätzen innerhalb einer Webanwendung. Das Projekt bindet Datenbank-Sitzungslebenszyklen an den aktiven Anwendungs-Request-Kontext, um eine automatische Verbindungsbereinigung sicherzustellen. Es bietet spezialisierte Utilities für den Web-Datenzugriff, einschließlich Query-Result-Pagination und einen Mechanismus, um automatisch 404-Not-Found-Antworten auszulösen, wenn ein angeforderter Datenbankdatensatz fehlt. Die Erweiterung deckt ein breites Spektrum an Datenbankverwaltungsfunktionen ab, einschließlich deklarativem Modell-Mapping, Schema-Reflektion und der Generierung physischer Tabellenstrukturen. Sie unterstützt fortgeschrittenes Verbindungsmanagement durch Multi-Bind-Query-Routing und bietet Observability-Tools zur Prüfung der SQL-Abfrageleistung und Ausführungszeit.
Supports adding custom methods to the query interface globally or on a per-model basis.
Flask-SQLAlchemy ist ein relationales Datenbank-Toolkit, das den SQLAlchemy Object-Relational-Mapper in Webanwendungen integriert. Es dient als Datenbank-Sitzungsmanager und Schema-Toolkit und stellt die notwendige Infrastruktur bereit, um Datenmodelle zu definieren und Abfragen innerhalb eines Request-Lebenszyklus auszuführen. Das Projekt zeichnet sich durch seine Multi-Datenbank-Routing-Engine aus, die Bind-Keys verwendet, um verschiedene Modelle auf mehrere unterschiedliche Datenbank-Engines abzubilden. Es enthält zudem ein SQL-Query-Auditing-Tool, das ausgeführte Statements und Zeitdaten für eine einzelne Anfrage erfasst und protokolliert, um Leistungsengpässe zu identifizieren. Das Toolkit deckt umfassende relationale Datenmodellierung und Schemamanagement ab, einschließlich der Möglichkeit, physische Tabellen aus Metadaten zu generieren oder bestehende Datenbankstrukturen zu reflektieren. Es verwaltet Verbindungslebenszyklen durch Request-scoped Sitzungsmanagement und bietet Utilities für Query-Result-Pagination und transaktionale Datenmodifikation.
Allows extending the query object with custom methods to streamline specialized data retrieval for models.
redb is an embedded key-value store and ACID-compliant storage engine. It functions as a persistent storage system for saving and retrieving data as key-value pairs within a tree structure. The engine is built as an MVCC transactional database, utilizing multi-version concurrency control to manage simultaneous reads and writes without blocking. It employs a single-writer multi-reader model to ensure data consistency while allowing multiple threads to access the store. The system provides persistent state management and atomic transaction management to prevent data corruption during crashes.
Provides a BTreeMap query interface for ordered key-value access without raw query syntax.