5 Repos
High-performance full-text search and retrieval using distributed document stores.
Distinct from Elasticsearch REST APIs: Closest candidates are limited to REST APIs or client-side documentation search.
Explore 5 awesome GitHub repositories matching data & databases · Distributed Document Indexing. Refine with filters or upvote what's useful.
OpenCTI is a cyber threat intelligence platform and knowledge base used to store, manage, and analyze technical security data. It functions as a threat intelligence visualization tool and an enterprise security data orchestrator that maps relationships between threat actors, malware, and vulnerabilities. The platform utilizes the STIX and TAXII standards for data representation and exchange, allowing for the sharing and receiving of standardized intelligence bundles. It distinguishes itself by converting complex security information into visual relationship diagrams and geographic maps to ide
Utilizes Elasticsearch for high-performance full-text searching and retrieval of structured intelligence data.
The official Go client for Elasticsearch
Batches document operations into single requests for high-throughput indexing of large datasets.
Dieses Projekt ist ein Software Development Kit (SDK) und Cluster-Management-Tool für PHP. Es dient als SDK für Volltextsuche und Vektor-Suchschnittstelle, wodurch Anwendungen lexikalische, Fuzzy- und semantische Suchen auf indizierten Daten durchführen können. Die Bibliothek implementiert einen PSR-7-HTTP-Client, um die Kompatibilität zwischen verschiedenen Umgebungen durch standardisierte Messaging-Schnittstellen zu gewährleisten. Sie bietet eine spezialisierte Schnittstelle zum Abrufen von Embeddings und zur Durchführung semantischer Retrieval-Workflows unter Verwendung von Vektordaten. Der Funktionsumfang deckt eine breite Palette administrativer und operativer Aufgaben ab, einschließlich der Verwaltung von Suchindizes, der Überwachung des Cluster-Status und der Verwaltung von Dokumentlebenszyklen. Es unterstützt diverse Abfragemethoden wie SQL, EQL und ES|QL sowie Datenaggregation und Geodatenanalyse. Zusätzlich bietet es Tools für Machine-Learning-Orchestrierung, Anomalieerkennung sowie Identitäts- und Zugriffsmanagement.
Implements high-throughput operations for indexing documents individually or in bulk batches.
This project is a programmatic client for managing the lifecycle of documents within a distributed JSON search engine. It provides an Elasticsearch search client for indexing documents and performing complex queries, alongside a low-level client that acts as a flexible wrapper for sending raw HTTP requests to a cluster. The client features a fluent request builder that maps typed requests to REST API endpoints and a generic mapping layer to transform JSON responses into strongly typed objects. It employs a pluggable serialization mechanism to decouple the request-response lifecycle from speci
Stores individual data records within specific indexes to make them available for retrieval.
The server acts as a centralized ingestion engine designed to collect, normalize, and index distributed telemetry data. It functions as a backend processor that receives performance metrics, traces, and error logs from application agents, transforming them into structured documents for storage and analysis within search and analytics platforms. The system distinguishes itself through a high-throughput ingestion pipeline that utilizes asynchronous event processing and backpressure-aware flow control to maintain stability during traffic spikes. It employs modular, plugin-based transformation st
Groups processed telemetry events into optimized batches to maximize write throughput to the search engine.