Powerful Search Included
ArangoSearch is a powerful search and similarity ranking engine natively integrated into ArangoDB. Combine search with any other data model.
“Quote about Using ArangoDB with integrated search”
– Customer Name, Company
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Feature-Rich, Accurate & Ranked Search
Legacy Graph DBs
Commodity graph databases lack the
extensive language support and
language-specific optimizations offered by
ArangoSearch.
This could lead to challenges in efficiently
searching and retrieving information across
different languages, potentially limiting the
user base and hindering global accessibility.
ArangoDB
ArangoSearch supports more than 30
languages including English, most european
languages and also Chinese.
Use dedicated language analyzers, as well as
stemming and stopword removal for fast and
efficient search in all supported languages.
Provide Search for Everyone
Commodity Graph DBs
Commodity graph databases don’t provide
integrated search capabilities and ranking
algorithms.
The result: less accurate and less finely
ranked search results, impacting the quality of
user experience and decision-making based
on search outcomes.
ArangoDB
Perform highly efficient search with C++
based ArangoSearch.
Use many query types spanning phrase,
wildcard, proximity, range and much more.
Rank your results by similarity using BM25 or
TFIDF algorithms.
Find Relevant Results to Fuzzy Searches
Legacy Graph DBs
The absence of advanced fuzzy search algorithms like ngram and Levenshtein in commodity graph DBs hinders the ability to find relevant results for non-exact matching queries.
This inhibits scenarios involving mobile applications, scientific data, or use cases where approximate matches are common.
ArangoDB
Provide highly relevant results for your users despite typos and other non-exact matching. Fuzzy search in ArangoSearch lets you use
ngram and Levenshtein algorithms to find the best approximate results.
Great for supporting search in mobile, scientific, bioinformatics and many other use cases.
Search Across Multiple Sources
Commodity Graph DBs
The absence of advanced fuzzy search algorithms like ngram and Levenshtein in commodity graph DBs hinders the ability to find relevant results for non-exact matching queries.
This inhibits scenarios involving mobile applications, scientific data, or use cases where approximate matches are common.
ArangoDB
Perform Multi-Model Graph Searches Extend your ArangoSearch queries with graph, geo or relational-type aspects for even more
fine-grained access to your data.
The flexibility of native multi-model combined with search is a powerful companion for many projects and simplifies your deployment stack.
Perform Multi-Model Graph Searches
Commodity Graph DBs
commodity graph databases require separate systems or complex integrations to achieve anything approaching ArangoDB’s multi-model
search functionalities.
This could result in a more convoluted architecture and increased development
efforts.
ArangoDB
ArangoSearch supports schema-agnostic indexing for allowing maximum flexibility within your search queries.
Combine even complex search across attributes & collections with all supported data models in ArangoDB.
Enterprise
Security
with no credit card required.
Download the
Baseline Graph DB
Requirements E-Book
Baseline Graph DB
Requirements E-Book
Read The
Case Studies
Case Studies
about how companies across industries are switching to Graph.