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DBMS > HugeGraph vs. LMDB vs. Neo4j vs. Sphinx

System Properties Comparison HugeGraph vs. LMDB vs. Neo4j vs. Sphinx

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Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonLMDB  Xexclude from comparisonNeo4j  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA fast-speed and highly-scalable Graph DBMSA high performant, light-weight, embedded key-value database libraryScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelGraph DBMSKey-value storeGraph DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score2.09
Rank#121  Overall
#20  Key-value stores
Score44.89
Rank#21  Overall
#1  Graph DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitegithub.com/­hugegraph
hugegraph.apache.org
www.symas.com/­symas-embedded-database-lmdbneo4j.comsphinxsearch.com
Technical documentationhugegraph.apache.org/­docswww.lmdb.tech/­docneo4j.com/­docssphinxsearch.com/­docs
DeveloperBaiduSymasNeo4j, Inc.Sphinx Technologies Inc.
Initial release2018201120072001
Current release0.90.9.32, January 20245.20, May 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoGPL version3, commercial licenses availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageJavaCJava, ScalaC++
Server operating systemsLinux
macOS
Unix
Linux
Unix
Windows
Linux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-free and schema-optionalyes
Typing infopredefined data types such as float or dateyesyesno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesyes infoalso supports composite index and range indexnoyes infopluggable indexing subsystem, by default Apache Luceneyes infofull-text index on all search fields
SQL infoSupport of SQLnononoSQL-like query language (SphinxQL)
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Proprietary protocol
Supported programming languagesGroovy
Java
Python
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsnoyes infoUser defined Procedures and Functionsno
Triggersnonoyes infovia event handlerno
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBasenoneyes using Neo4j FabricSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBasenoneCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integrityyes infoedges in graphnoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlUsers, roles and permissionsnoUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)no
More information provided by the system vendor
HugeGraphLMDBNeo4jSphinx
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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