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DBMS > AgensGraph vs. Citus vs. Datomic vs. Google Cloud Bigtable vs. Linter

System Properties Comparison AgensGraph vs. Citus vs. Datomic vs. Google Cloud Bigtable vs. Linter

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonCitus  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.RDBMS for high security requirements
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSRelational DBMSKey-value store
Wide column store
Relational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.12
Rank#350  Overall
#152  Relational DBMS
Websitebitnine.net/­agensgraphwww.citusdata.comwww.datomic.comcloud.google.com/­bigtablelinter.ru
Technical documentationbitnine.net/­documentationdocs.citusdata.comdocs.datomic.comcloud.google.com/­bigtable/­docs
DeveloperBitnine Global Inc.CognitectGooglerelex.ru
Initial release20162010201220151990
Current release2.1, December 20188.1, December 20181.0.7075, December 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoAGPL, commercial license also availablecommercial infolimited edition freecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCCJava, ClojureC and C++
Server operating systemsLinux
OS X
Windows
LinuxAll OS with a Java VMhostedAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemedepending on used data modelyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLyesyes infostandard, with numerous extensionsnonoyes
APIs and other access methodsCypher Query Language
JDBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languagesC
Java
JavaScript
Python
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Clojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infoTransaction Functionsnoyes infoproprietary syntax with the possibility to convert from PL/SQL
TriggersnoyesBy using transaction functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingnone infoBut extensive use of caching in the application peersShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensionsnone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes inforecommended only for testing and developmentno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
AgensGraphCitusDatomicGoogle Cloud BigtableLinter
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