Search Results for "index and search"

Zinc 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. You can index large amounts of text Zinc and search instantly. Zinc is a batteries-included setup. Embedded UI provides an easy...

Import one package, build an index with three lines of code, query for documents with another three lines. Bleve includes general-purpose analyzers as well as pre-built text analyzers for the following languages, Danish, Dutch, English, Finnish, French, German, Hungarian, Italian, Norwegian, Persian, Portuguese, Romanian, Russian, Sorani, Spanish, Swedish, Thai, and Turkish. Support for aggregating facet information across search results. Supported facet types include Terms Facet, Numeric Range...

Vearch is the vector search infrastructure for deep learning and AI applications. Vearch is a distributed vector storage and retrieval system which can be easily extended to billions scale. Vearch implements a high-performance, lockless real-time vector indexing subsystem that utilizes various optimization techniques to support millisecond vector update and retrieval. End-to-end one-click deployment. Through the module of the plugin, a complete default visual search system can be deployed just...

Vald is a highly scalable distributed fast approximate nearest neighbor dense vector search engine. Vald is designed and implemented based on the Cloud-Native architecture. It uses the fastest ANN Algorithm NGT to search for neighbors. Vald has automatic vector indexing and index backup, and horizontal scaling which is made for searching from billions of feature vector data. Vald is easy to use, feature-rich and highly customizable as you needed. Usually, the graph requires locking during...

An Elasticsearch client for the Go programming language. Elastic supports different versions of Elasticsearch. However, you must choose the version of Elastic that matches the Elasticsearch version. If you want to use stable versions of Elastic, please use Go modules for the 7.x release (or later) or a dependency manager like dep for earlier releases. Elastic has been used in production starting with Elasticsearch 0.90 up to recent 7.x versions. We recently switched to GitHub Actions for...

Go Open Source, Distributed, Simple and efficient full text search engine. Efficient indexing and search (1M blog 500M data 28 seconds index finished, 1.65 ms search response time, 19K search QPS). Support for logical search. Support Chinese word segmentation (use gse word segmentation package concurrent word, speed 27MB / s). Support the calculation of the keyword in the text close to the distance（token proximity). Support calculation BM25 correlation. Support custom scoring field and scoring...

... the search index (while the server is stopped), and an administrative command, for manipulating users.

Efficient indexing and searching (1M Weibo 500M data is indexed in 28 seconds, search response time is 1.65 milliseconds, and search QPS is 19K). Support Chinese word segmentation (concurrent word segmentation using the sego word segmentation package, speed 27MB/sec). Support to calculate the proximity distance of keywords in the text (token proximity). When a request to add a document to the index comes in, the main coroutine will send the text to be segmented to a word segmentation coroutine...