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DBMS > BigObject vs. Citus vs. Fujitsu Enterprise Postgres vs. HugeGraph vs. Realm

System Properties Comparison BigObject vs. Citus vs. Fujitsu Enterprise Postgres vs. HugeGraph vs. Realm

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonCitus  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonHugeGraph  Xexclude from comparisonRealm  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.A fast-speed and highly-scalable Graph DBMSA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSRelational DBMSGraph DBMSDocument store
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Websitebigobject.iowww.citusdata.comwww.postgresql.fastware.comgithub.com/­hugegraph
hugegraph.apache.org
realm.io
Technical documentationdocs.bigobject.iodocs.citusdata.comwww.postgresql.fastware.com/­product-manualshugegraph.apache.org/­docsrealm.io/­docs
DeveloperBigObject, Inc.PostgreSQL Global Development Group, Fujitsu Australia Software TechnologyBaiduRealm, acquired by MongoDB in May 2019
Initial release2015201020182014
Current release8.1, December 2018Fujitsu Enterprise Postgres 14, January 20220.9
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache Version 2.0Open Source
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCCJava
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxLinux
Windows
Linux
macOS
Unix
Android
Backend: server-less
iOS
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 functionalitynono
Secondary indexesyesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard, with numerous extensionsyesnono
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Groovy
Java
Python
.Net
Java infowith Android only
Objective-C
React Native
Swift
Server-side scripts infoStored proceduresLuauser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functionsasynchronous Gremlin script jobsno inforuns within the applications so server-side scripts are unnecessary
Triggersnoyesyesnoyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesnoneShardingpartitioning by range, list and by hashyes infodepending on used storage backend, e.g. Cassandra and HBasenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replicationyes infodepending on used storage backend, e.g. Cassandra and HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononovia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesyesyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyes, multi-version concurrency control (MVCC)yes
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.yesnoyesyes infoIn-Memory realm
User concepts infoAccess controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standardUsers, roles and permissionsyes
More information provided by the system vendor
BigObjectCitusFujitsu Enterprise PostgresHugeGraphRealm
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
BigObjectCitusFujitsu Enterprise PostgresHugeGraphRealm
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