Milvus vs Searchkick
Overview
Detailed Comparison
Searchkick learns what your users are looking for. As more people search, it gets smarter and the results get better. It’s friendly for developers - and magical for your users. | Milvus is an open source vector database. Built with heterogeneous computing architecture for the best cost efficiency. Searches over billion-scale vectors take only milliseconds with minimum computing resources. |
stemming - tomatoes matches tomato;special characters - jalapeno matches jalapeño;extra whitespace - dishwasher matches dish washer;misspellings - zuchini matches zucchini;custom synonyms - qtip matches cotton swab;query like SQL - no need to learn a new query language;reindex without downtime;easily personalize results for each user;autocomplete;“Did you mean” suggestions;works with ActiveRecord and Mongoid | Heterogeneous computing; Multiple indexes; Intelligent resource management; Horizontal scalability; High availability |
Statistics | |
GitHub Stars 6.7K | GitHub Stars 38.3K |
GitHub Forks 766 | GitHub Forks 3.5K |
Stacks 17 | Stacks 57 |
Followers 34 | Followers 49 |
Votes 1 | Votes 2 |
Pros & Cons | |
Pros
| Pros
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Integrations | |
| No integrations available | |
What are some alternatives to Searchkick, Milvus?
Sphinx
It lets you either batch index and search data stored in an SQL database, NoSQL storage, or just files quickly and easily — or index and search data on the fly, working with it pretty much as with a database server.
MkDocs
It builds completely static HTML sites that you can host on GitHub pages, Amazon S3, or anywhere else you choose. There's a stack of good looking themes available. The built-in dev-server allows you to preview your documentation as you're writing it. It will even auto-reload and refresh your browser whenever you save your changes.
Lucene
Lucene Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities.
Search the world's information, including webpages, images, videos and more. Google has many special features to help you find exactly what you're looking for.
YugabyteDB
An open-source, high-performance, distributed SQL database built for resilience and scale. Re-uses the upper half of PostgreSQL to offer advanced RDBMS features, architected to be fully distributed like Google Spanner.
Apache Solr
It uses the tools you use to make application building a snap. It is built on the battle-tested Apache Zookeeper, it makes it easy to scale up and down.
Qdrant
It is an open-source Vector Search Engine and Vector Database written in Rust. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more.
Chroma
It is an open-source embedding database. Chroma makes it easy to build LLM apps by making knowledge, facts, and skills pluggable for LLMs.
Weaviate
It is an open-source vector search engine. It allows you to store data objects and vector embeddings from your favorite ML-models, and scale seamlessly into billions of data objects.
AddSearch
We help your website visitors find what they are looking for. AddSearch is a lightning fast, accurate and customizable site search engine with a Search API. AddSearch works on all devices and is easy to install, customize and tweak.
