Heliosearch is a high-performance NoSQL search server, the next generation of Solr open source search.


Heliosearch/Solr Features

High-Performance Architecture


In addition to the query-parameter request APIs of Solr, Heliosearch adds:

Document Oriented

Document oriented storage enables high scalability. Solr is data-format agnostic, and does is not tied to any particular serialization. Documents can be added to Solr in JSON, XML, CSV, or binary format.


Split a big index across multiple machines and query it as if it were a single document collection.

Fault Tolerant

There are no single points of failure. Documents are replicated to multiple nodes for fault-tolerance, high availability, and increased query scalability.

Atomic Updates

Atomic field modifiers for highly scalable document modification.

Optimistic Concurrency

Versioning and conditionally updates based on document versions.

Faceted Search & Realtime Analytics

Dynamic category counting for search results, including nested faceting and calculation of other statistics. Slice-and-dice data on the fly!
New in Heliosearch: faceting enhancements including

Hit Highlighting

Also called “keyword in context”, this feature returns snippets of documents with matching query terms highlighted.

Spatial Search

Find documents within a certain distance from a given point on Earth.

Full-text Search

Solr uses Lucene as it’s primary index format to provide world class full-text search capabilities.


Although Solr is primarily document oriented, we recognize that certain database operations like JOIN can be the right tool for the job in some circumstances. This functionality selects a set of documents based on their relationship to a second set of documents.


This feature limits the number of documents shown per category. For example, one could limit the number of website pages shown per domain or the number of pages shown per book.