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DBMS > Neo4j vs. Sphinx vs. Splice Machine vs. Yanza

System Properties Comparison Neo4j vs. Sphinx vs. Splice Machine vs. Yanza

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Editorial information provided by DB-Engines
NameNeo4j  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionScalable, 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 databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTime Series DBMS for IoT Applications
Primary database modelGraph DBMSSearch engineRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score44.46
Rank#23  Overall
#1  Graph DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteneo4j.comsphinxsearch.comsplicemachine.comyanza.com
Technical documentationneo4j.com/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperNeo4j, Inc.Sphinx Technologies Inc.Splice MachineYanza
Initial release2007200120142015
Current release5.19, April 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoGPL version3, commercial licenses availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
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 languageJava, ScalaC++Java
Server operating systemsLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Windows
Data schemeschema-free and schema-optionalyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesno
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.no
Secondary indexesyes infopluggable indexing subsystem, by default Apache Luceneyes infofull-text index on all search fieldsyesno
SQL infoSupport of SQLnoSQL-like query language (SphinxQL)yesno
APIs and other access methodsBolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Proprietary protocolJDBC
Native Spark Datasource
ODBC
HTTP API
Supported programming languages.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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresyes infoUser defined Procedures and Functionsnoyes infoJavano
Triggersyes infovia event handlernoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesyes using Neo4j FabricSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlynoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)noAccess rights for users, groups and roles according to SQL-standardno
More information provided by the system vendor
Neo4jSphinxSplice MachineYanza
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
News

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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