Skip to content

ZincSearch . A lightweight alternative to elasticsearch that requires minimal resources, written in Go.

License

Notifications You must be signed in to change notification settings

ershat123/zincsearch

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Go Report Card Docs codecov

❗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 zinclabs/zincobserve project built in rust that is specifically built for log search use case.

ZincSearch

ZincSearch 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 as the underlying indexing library.

It 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

It 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).

Check the below video for a quick demo of ZincSearch.

Zinc Youtube

Why ZincSearch

While 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.

Features:

  1. Provides full text indexing capability
  2. Single binary for installation and running. Binaries available under releases for multiple platforms.
  3. Web UI for querying data written in Vue
  4. Compatibility with Elasticsearch APIs for ingestion of data (single record and bulk API)
  5. Out of the box authentication
  6. Schema less - No need to define schema upfront and different documents in the same index can have different fields.
  7. Index storage in disk
  8. aggregation support

Documentation

Documentation is available at https://zincsearch-docs.zinc.dev/

Screenshots

Search screen

Search screen

User management screen

Users screen

Getting started

Quickstart

Check Quickstart

Releases

ZincSearch has hundreds of production installations is in GA.

ZincSearch Vs ZincObserve

Feature ZincSearch ZincObserve
Ideal use case App search Logs, metrics, traces (Immutable Data)
Storage Disk Disk, Object (S3), GCS, MinIO, swift and more.
Preferred Use case App search Observability (Logs, metrics, traces)
Max data supported 100s of GBs Petabyte scale
High availability Not available Yes
Open source Yes Yes, ZincObserve
ES API compatibility Yes Yes
GUI Basic Very Advanced, including dashboards
Cost Open source Open source
Get started Open source docs Open source docs or Cloud

Community

Examples

You 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:

  1. https://github.com/jorgeloaiza48/Enron-Email-DataSet
  2. https://github.com/jhojanperlaza/email_search_engine
  3. https://github.com/carlosarraes/zinmail
  4. https://github.com/devjopa/golab-search
  5. https://github.com/avaco2312/zincsearch
  6. https://github.com/paolorossig/email-indexer

About

ZincSearch . A lightweight alternative to elasticsearch that requires minimal resources, written in Go.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Go 93.4%
  • Vue 4.6%
  • TypeScript 1.4%
  • Shell 0.3%
  • Dockerfile 0.1%
  • JavaScript 0.1%
  • Other 0.1%