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DBMS > BigObject vs. Citus vs. GridGain vs. Hazelcast vs. Linter

System Properties Comparison BigObject vs. Citus vs. GridGain vs. Hazelcast vs. Linter

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonCitus  Xexclude from comparisonGridGain  Xexclude from comparisonHazelcast  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionAnalytic DBMS for real-time computations and queriesScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLGridGain is an in-memory computing platform, built on Apache IgniteA widely adopted in-memory data gridRDBMS for high security requirements
Primary database modelRelational DBMS infoa hierachical model (tree) can be imposedRelational DBMSKey-value store
Relational DBMS
Key-value storeRelational DBMS
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.09
Rank#346  Overall
#152  Relational DBMS
Websitebigobject.iowww.citusdata.comwww.gridgain.comhazelcast.comlinter.ru
Technical documentationdocs.bigobject.iodocs.citusdata.comwww.gridgain.com/­docs/­index.htmlhazelcast.org/­imdg/­docs
DeveloperBigObject, Inc.GridGain Systems, Inc.Hazelcastrelex.ru
Initial release20152010200720081990
Current release8.1, December 2018GridGain 8.5.15.3.6, November 2023
License infoCommercial or Open Sourcecommercial infofree community edition availableOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial
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 languageCJava, C++, .NetJavaC and C++
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxLinux
OS X
Solaris
Windows
All OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesyesyesschema-freeyes
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 functionalityyesyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard, with numerous extensionsANSI-99 for query and DML statements, subset of DDLSQL-like query languageyes
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresLuauser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes (compute grid and cache interceptors can be used instead)yes infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersnoyesyes (cache interceptors and events)yes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication infoother methods possible by using 3rd party extensionsyes (replicated cache)yes infoReplicated MapSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (compute grid and hadoop accelerator)yesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDone or two-phase-commit; repeatable reads; read commitedACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyesyes
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
User concepts infoAccess controlnofine grained access rights according to SQL-standardSecurity Hooks for custom implementationsRole-based access controlfine grained access rights according to SQL-standard

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More resources
BigObjectCitusGridGainHazelcastLinter
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