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DBMS > Hive vs. Neo4j vs. Spark SQL vs. Trafodion

System Properties Comparison Hive vs. Neo4j vs. Spark SQL vs. Trafodion

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonNeo4j  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSGraph DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score44.46
Rank#23  Overall
#1  Graph DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitehive.apache.orgneo4j.comspark.apache.org/­sqltrafodion.apache.org
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homeneo4j.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperApache Software Foundation infoinitially developed by FacebookNeo4j, Inc.Apache Software FoundationApache Software Foundation, originally developed by HP
Initial release2012200720142014
Current release3.1.3, April 20225.19, April 20243.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGPL version3, commercial licenses availableOpen Source infoApache 2.0Open Source infoApache 2.0
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 languageJavaJava, ScalaScalaC++, Java
Server operating systemsAll OS with a Java VMLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
Data schemeyesschema-free and schema-optionalyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyes infopluggable indexing subsystem, by default Apache Lucenenoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
Thrift
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoUser defined Procedures and FunctionsnoJava Stored Procedures
Triggersnoyes infovia event handlernono
Partitioning methods infoMethods for storing different data on different nodesShardingyes using Neo4j Fabricyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlynoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and rolesUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)nofine grained access rights according to SQL-standard
More information provided by the system vendor
HiveNeo4jSpark SQLTrafodion
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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