[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-4838":3},{"id":4,"name":5,"fullName":6,"owner":5,"repo":5,"description":7,"homepage":8,"htmlUrl":9,"language":10,"languages":9,"totalLinesOfCode":9,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":15,"stars7d":16,"stars30d":17,"stars90d":15,"forks30d":15,"starsTrendScore":18,"compositeScore":19,"rankGlobal":9,"rankLanguage":9,"license":20,"archived":21,"fork":21,"defaultBranch":22,"hasWiki":23,"hasPages":21,"topics":24,"createdAt":9,"pushedAt":9,"updatedAt":33,"readmeContent":34,"aiSummary":35,"trendingCount":15,"starSnapshotCount":15,"syncStatus":18,"lastSyncTime":36,"discoverSource":37},4838,"zincsearch","zincsearch\u002Fzincsearch","ZincSearch . A lightweight alternative to elasticsearch that requires minimal resources, written in Go.","https:\u002F\u002Fzincsearch-docs.zinc.dev",null,"Go",17845,773,155,45,0,5,29,2,43.67,"Other",false,"main",true,[25,26,27,28,29,30,31,32],"elasticsearch","go","golang","modern","opensearch","search","searchengine","vuejs","2026-06-12 02:01:04","[![Go Report Card](https:\u002F\u002Fgoreportcard.com\u002Fbadge\u002Fgithub.com\u002Fzincsearch\u002Fzincsearch)](https:\u002F\u002Fgoreportcard.com\u002Freport\u002Fgithub.com\u002Fzincsearch\u002Fzincsearch)\n[![Docs](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FDocs-Docs-green)](https:\u002F\u002Fzincsearch-docs.zinc.dev\u002F) [![codecov](https:\u002F\u002Fcodecov.io\u002Fgithub\u002Fzincsearch\u002Fzincsearch\u002Fbranch\u002Fmain\u002Fgraph\u002Fbadge.svg)](https:\u002F\u002Fcodecov.io\u002Fgithub\u002Fzinclabs\u002Fzincsearch)\n\n❗Note: If your use case is of log search (app and security logs) instead of app search (implement search feature in your application or website) then you should check [openobserve\u002Fopenobserve](https:\u002F\u002Fgithub.com\u002Fopenobserve\u002Fopenobserve) project built in rust that is specifically built for log search use case.\n\n# ZincSearch\n\nZincSearch is a search engine that does full text indexing. It is a lightweight alternative to Elasticsearch and runs using a fraction of the resources. It uses [bluge](https:\u002F\u002Fgithub.com\u002Fblugelabs\u002Fbluge) as the underlying indexing library.\n\nIt is very simple and easy to operate as opposed to Elasticsearch which requires a couple dozen knobs to understand and tune which you can get up and running in 2 minutes\n\nIt is a drop-in replacement for Elasticsearch if you are just ingesting data using APIs and searching using kibana (Kibana is not supported with ZincSearch. ZincSearch provides its own UI).\n\nCheck the below video for a quick demo of ZincSearch.\n\n[![Zinc Youtube](.\u002Fscreenshots\u002Fzinc-youtube.jpg)](https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=aZXtuVjt1ow)\n\n# Why ZincSearch\n\nWhile Elasticsearch is a very good product, it is complex and requires lots of resources and is more than a decade old. I built ZincSearch so it becomes easier for folks to use full text search indexing without doing a lot of work.\n\n# Features:\n\n1. Provides full text indexing capability\n2. Single binary for installation and running. Binaries available under releases for multiple platforms.\n3. Web UI for querying data written in Vue\n4. Compatibility with Elasticsearch APIs for ingestion of data (single record and bulk API)\n5. Out of the box authentication\n6. Schema less - No need to define schema upfront and different documents in the same index can have different fields.\n7. Index storage in disk\n8. aggregation support\n\n# Documentation\n\nDocumentation is available at [https:\u002F\u002Fzincsearch-docs.zinc.dev\u002F](https:\u002F\u002Fzincsearch-docs.zinc.dev\u002F)\n\n# Screenshots\n\n## Search screen\n\n![Search screen](.\u002Fscreenshots\u002Fsearch_screen.jpg)\n\n## User management screen\n\n![Users screen](.\u002Fscreenshots\u002Fusers_screen.jpg)\n\n# Getting started\n\n## Quickstart\n\nCheck [Quickstart](https:\u002F\u002Fzincsearch-docs.zinc.dev\u002Fquickstart\u002F)\n\n# Releases\n\nZincSearch has hundreds of production installations.\n\n# ZincSearch Vs OpenObserve\n\n| Feature              | ZincSearch                                                       | OpenObserve                                                                               |\n| -------------------- | ---------------------------------------------------------------- | ----------------------------------------------------------------------------------------- |\n| Ideal use case       | App search                                                       | Logs, metrics, traces (Immutable Data)                                                    |\n| Storage              | Disk                                                             | Disk, Object (S3), GCS, MinIO, swift and more.                                            |\n| Preferred Use case   | App search                                                       | Observability (Logs, metrics, traces)                                                     |\n| Max data supported   | 100s of GBs                                                      | Petabyte scale                                                                            |\n| High availability    | Not available                                                    | Yes                                                                                       |\n| Open source          | Yes                                                              | Yes, [OpenObserve](https:\u002F\u002Fgithub.com\u002Fopenobserve\u002Fopenobserve)                            |\n| ES API compatibility | Yes                                                              | Yes                                                                                       |\n| GUI                  | Basic                                                            | Very Advanced, including dashboards                                                       |\n| Cost                 | Open source                                                      | Open source                                                                               |\n| Get started          | [Open source docs](https:\u002F\u002Fzincsearch-docs.zinc.dev\u002Fquickstart\u002F) | [Open source docs](https:\u002F\u002Fopenobserve.ai\u002Fdocs) or [Cloud](https:\u002F\u002Fcloud.openobserve.ai) |\n\n# Community\n\n- How to develop and contribute to ZincSearch\n\n  Check the [contributing guide](.\u002FCONTRIBUTING.md) . Also check the [roadmap items](https:\u002F\u002Fgithub.com\u002Forgs\u002Fzinclabs\u002Fprojects\u002F3)\n\n# Examples\n\nYou can use ZincSearch to index and search any data. Here are some examples that folks have created to index and search enron email dataset using zincsearch:\n\n1. https:\u002F\u002Fgithub.com\u002Fjorgeloaiza48\u002FEnron-Email-DataSet\n1. https:\u002F\u002Fgithub.com\u002Fjhojanperlaza\u002Femail_search_engine\n1. https:\u002F\u002Fgithub.com\u002Fcarlosarraes\u002Fzinmail\n1. https:\u002F\u002Fgithub.com\u002Fdevjopa\u002Fgolab-search\n1. https:\u002F\u002Fgithub.com\u002Favaco2312\u002Fzincsearch\n1. https:\u002F\u002Fgithub.com\u002Fpaolorossig\u002Femail-indexer\n1. https:\u002F\u002Fgithub.com\u002Fulimonte05\u002Fzincsearching\n","ZincSearch 是一个轻量级的全文搜索引擎，旨在作为 Elasticsearch 的替代方案，使用更少的资源。其核心功能包括全文索引、与 Elasticsearch API 兼容的数据导入（支持单条记录和批量API）、开箱即用的身份验证机制以及无模式设计，允许同一索引内的文档拥有不同的字段。此外，ZincSearch 提供了一个基于 Vue.js 开发的Web界面用于数据查询，并且只需单一二进制文件即可完成安装和运行。该项目非常适合需要快速部署搜索功能但又不想投入大量硬件资源或时间进行复杂配置的小型至中型企业应用环境。","2026-06-11 03:00:47","top_language"]