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DBMS > BigObject vs. Citus vs. Google Cloud Datastore vs. HugeGraph vs. Realm

System Properties Comparison BigObject vs. Citus vs. Google Cloud Datastore vs. HugeGraph vs. Realm

Editorial information provided by DB-Engines
NameBigObject  Xexclude from comparisonCitus  Xexclude from comparisonGoogle Cloud Datastore  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 PostgreSQLAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA 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 DBMSDocument storeGraph DBMSDocument store
Secondary database modelsDocument store
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
Score4.36
Rank#72  Overall
#12  Document stores
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Websitebigobject.iowww.citusdata.comcloud.google.com/­datastoregithub.com/­hugegraph
hugegraph.apache.org
realm.io
Technical documentationdocs.bigobject.iodocs.citusdata.comcloud.google.com/­datastore/­docshugegraph.apache.org/­docsrealm.io/­docs
DeveloperBigObject, Inc.GoogleBaiduRealm, acquired by MongoDB in May 2019
Initial release20152010200820182014
Current release8.1, December 20180.9
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 servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava
Server operating systemsLinux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
LinuxhostedLinux
macOS
Unix
Android
Backend: server-less
iOS
Windows
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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 functionalitynonono
Secondary indexesyesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard, with numerous extensionsSQL-like query language (GQL)nono
APIs and other access methodsfluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
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.using Google App Engineasynchronous Gremlin script jobsno inforuns within the applications so server-side scripts are unnecessary
TriggersnoyesCallbacks using the Google Apps Enginenoyes infoChange Listeners
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes 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 extensionsMulti-source replication using Paxosyes infodepending on used storage backend, e.g. Cassandra and HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoautomatically between fact table and dimension tablesyesyes infovia ReferenceProperties or Ancestor pathsyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayes infoRead/write lock on objects (tables, trees)yesyesyes
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.yesnonoyesyes infoIn-Memory realm
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsyes

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More resources
BigObjectCitusGoogle Cloud DatastoreHugeGraphRealm
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