zincsearch/zincsearch

Features

• Elasticsearch Compatible Engines - Serves as a lightweight Go-based alternative to Elasticsearch while maintaining API compatibility.
• Text Tokenizers - Processes raw text into searchable tokens using a pipeline of analyzers and filters before indexing.
• Document Management - Provides capabilities for creating, updating, and deleting individual documents within a specified index.
• Bulk Data Ingestion - Processes multiple document additions or deletions in a single request to increase ingestion speed.
• Inverted Index Engines - Utilizes inverted-index storage to map terms to document IDs for fast full-text retrieval.
• Full-Text Search Engines - Provides a resource-efficient system for indexing and searching unstructured text data.
• Schemaless Data Stores - Stores records without predefined tables by dynamically mapping fields during the indexing process.
• Search Index Management - Provides administrative control to create, retrieve, and delete indices while defining field mappings.
• Search and Indexing - Combines data indexing capabilities with search functionality to enable fast lookup of unstructured text.
• Elasticsearch REST APIs - Implements RESTful endpoints mirroring Elasticsearch to allow seamless integration with existing search tools.
• Text Search Databases - Provides a specialized database for indexing and retrieving unstructured text using fuzzy and wildcard queries.
• Self-Hosted Search Services - Offers a private, containerized search engine deployment that ensures data privacy and isolated execution.
• Data Ingestion APIs - Offers a standard interface for accepting data records to simplify the integration of external information sources.
• Go Search Servers - Implements a high-performance search engine written in Go with an integrated web interface for data exploration.
• Advanced Query Types - Supports advanced document retrieval using fuzzy, wildcard, phrase, and range queries.
• Search Result Aggregators - Groups and summarizes indexed data to produce counts and statistical insights across the dataset.
• Text Processing Pipelines - Implements a modular pipeline using tokenizers and filters to prepare raw text for efficient indexing.
• Single-Binary Distributions - Packages the entire server and management tools into a single statically linked executable.
• Binary Asset Embedding - Bakes the web user interface files directly into the compiled binary for single-file deployment.
• User Account Management - Includes a system for controlling access through the creation and maintenance of user profiles.
• Log Analysis - Provides tools for parsing and interpreting logs to extract statistical insights and patterns from large datasets.
• Web Search Interfaces - Includes a built-in graphical user interface for executing searches and exploring indexed data.
• Databases and Storage - Lightweight alternative to Elasticsearch.

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