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DBMS > Hive vs. NuoDB vs. PostgreSQL vs. Realm vs. Spark SQL

System Properties Comparison Hive vs. NuoDB vs. PostgreSQL vs. Realm vs. Spark SQL

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonNuoDB  Xexclude from comparisonPostgreSQL  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopNuoDB is a webscale distributed database that supports SQL and ACID transactionsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Document storeRelational DBMS
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.94
Rank#197  Overall
#92  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitehive.apache.orgwww.3ds.com/­nuodb-distributed-sql-databasewww.postgresql.orgrealm.iospark.apache.org/­sql
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedoc.nuodb.comwww.postgresql.org/­docsrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoinitially developed by FacebookDassault Systèmes infooriginally NuoDB, Inc.PostgreSQL Global Development Group infowww.postgresql.org/­developerRealm, acquired by MongoDB in May 2019Apache Software Foundation
Initial release201220131989 info1989: Postgres, 1996: PostgreSQL20142014
Current release3.1.3, April 202216.3, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freeOpen Source infoBSDOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++CScala
Server operating systemsAll OS with a Java VMhosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Android
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infostandard with numerous extensionsnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Thrift
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesC++
Java
PHP
Python
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava, SQLuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no inforuns within the applications so server-side scripts are unnecessaryno
Triggersnoyesyesyes infoChange Listenersno
Partitioning methods infoMethods for storing different data on different nodesShardingdata is dynamically stored/cached on the nodes where it is read/writtenpartitioning by range, list and (since PostgreSQL 11) by hashnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoManaged transparently by NuoDBSource-replica replication infoother methods possible by using 3rd party extensionsnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infotunable commit protocolACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoTemporary tablenoyes infoIn-Memory realmno
User concepts infoAccess controlAccess rights for users, groups and rolesStandard SQL roles/ privileges, Administrative Usersfine grained access rights according to SQL-standardyesno

More information provided by the system vendor

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More resources
HiveNuoDBPostgreSQLRealmSpark SQL
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