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DBMS > Citus vs. EsgynDB vs. Google Cloud Bigtable vs. HugeGraph vs. InterSystems Caché

System Properties Comparison Citus vs. EsgynDB vs. Google Cloud Bigtable vs. HugeGraph vs. InterSystems Caché

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHugeGraph  Xexclude from comparisonInterSystems Caché  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A fast-speed and highly-scalable Graph DBMSA multi-model DBMS and application server
Primary database modelRelational DBMSRelational DBMSKey-value store
Wide column store
Graph DBMSKey-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitewww.citusdata.comwww.esgyn.cncloud.google.com/­bigtablegithub.com/­hugegraph
hugegraph.apache.org
www.intersystems.com/­products/­cache
Technical documentationdocs.citusdata.comcloud.google.com/­bigtable/­docshugegraph.apache.org/­docsdocs.intersystems.com
DeveloperEsgynGoogleBaiduInterSystems
Initial release20102015201520181997
Current release8.1, December 20180.92018.1.4, May 2020
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialOpen Source infoApache Version 2.0commercial
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 languageCC++, JavaJava
Server operating systemsLinuxLinuxhostedLinux
macOS
Unix
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyesdepending on used data model
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.yes infospecific XML type available, but no XML query functionalitynononoyes
Secondary indexesyesyesnoyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsyesnonoyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
TinkerPop Gremlin
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
C#
C++
Java
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Java Stored Proceduresnoasynchronous Gremlin script jobsyes
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nononoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine 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 permissionsAccess rights for users, groups and roles

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More resources
CitusEsgynDBGoogle Cloud BigtableHugeGraphInterSystems Caché
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