Algolia
Hosted search-as-a-service platform delivering real-time, full-text search for apps and websites
ZincSearch
Lightweight full-text search engine, drop-in Elasticsearch alternative
ZincSearch delivers full‑text indexing with a single binary, minimal resources, Elasticsearch‑compatible APIs, built‑in UI, and schema‑less operation—ready in minutes.
Overview
Overview
ZincSearch is a Go‑based full‑text search engine designed as a lightweight drop‑in replacement for Elasticsearch. It runs from a single binary, supports multiple platforms, and can be up and running in minutes with minimal configuration.
Capabilities
The engine provides schema‑less indexing, on‑disk storage, aggregation support, and out‑of‑the‑box authentication. It implements Elasticsearch’s ingest and search APIs, allowing existing clients to interact without code changes, while a built‑in Vue UI offers query editing and result visualization.
Deployment
Installation is as simple as downloading the appropriate binary and starting the service. Because it consumes a fraction of the resources required by Elasticsearch, it fits well on modest servers or containers. Production‑grade deployments are already in use across hundreds of installations, making ZincSearch a pragmatic choice for developers who need fast app‑search without the operational overhead of a full‑scale Elasticsearch cluster.
Highlights
Single binary, cross‑platform installation
Elasticsearch API compatibility for ingestion and search
Built‑in Vue UI with authentication
Schema‑less indexing and on‑disk storage
Pros
- Low resource consumption
- Simple, fast setup
- Compatible with Elasticsearch clients
- Flexible schema‑less data model
Considerations
- No built‑in high availability
- Limited to disk storage
- Basic UI compared to advanced observability tools
- No Kibana integration
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Fit guide
Great for
- Developers needing fast app‑search without managing Elasticsearch
- Small‑to‑medium services with limited hardware
- Teams that prefer a single binary deployment
- Projects that value schema‑less indexing
Not ideal when
- Large‑scale log or observability pipelines
- Petabyte‑scale data sets
- Environments requiring built‑in high availability
- Users needing Kibana‑style dashboards
How teams use it
Add search to a SaaS product
Users can instantly find documents, emails, or records via full‑text queries
Internal knowledge‑base search
Employees retrieve relevant articles without schema design
E‑commerce product catalog search
Fast, typo‑tolerant search across product listings
Simple analytics dashboard
Aggregations enable quick metrics on indexed data
Tech snapshot
Go93%
Vue5%
TypeScript1%
Shell1%
Dockerfile1%
JavaScript1%
Frequently asked questions
Is ZincSearch compatible with existing Elasticsearch clients?
Yes, it supports the same ingest and search REST APIs, so most Elasticsearch clients work without modification.
What operating systems are supported?
Pre‑compiled binaries are provided for Linux, macOS, and Windows.
How does authentication work?
ZincSearch includes built‑in user management with username/password and can be extended via external auth providers.
Can I run ZincSearch in a container?
Official Docker images are available, enabling easy deployment in Kubernetes or Docker environments.
Does ZincSearch provide high availability?
High‑availability clustering is not built in; deployments are single‑node unless external replication is added.
Project at a glance
Active- Stars
- 17,703
- Watchers
- 17,703
- Forks
- 764
Repo age4 years old
Last commit2 months ago
Primary languageGo
Last synced yesterday