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DBMS > Citus vs. Google Cloud Spanner vs. Hazelcast vs. Linter

System Properties Comparison Citus vs. Google Cloud Spanner vs. Hazelcast vs. Linter

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHazelcast  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A widely adopted in-memory data gridRDBMS for high security requirements
Primary database modelRelational DBMSRelational DBMSKey-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
Score2.21
Rank#129  Overall
#61  Relational DBMS
Score3.37
Rank#97  Overall
#50  Relational DBMS
Score7.66
Rank#54  Overall
#5  Key-value stores
Score0.15
Rank#339  Overall
#147  Relational DBMS
Websitewww.citusdata.comcloud.google.com/­spannerhazelcast.comlinter.ru
Technical documentationdocs.citusdata.comcloud.google.com/­spanner/­docshazelcast.org/­imdg/­docs
DeveloperGoogleHazelcastrelex.ru
Initial release2010201720081990
Current release8.1, December 20185.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaC and C++
Server operating systemsLinuxhostedAll OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 functionalitynoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsyes infoQuery statements complying to ANSI 2011SQL-like query languageyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
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
Go
Java
JavaScript (Node.js)
Python
.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 proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersyesnoyes infoEventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication with 3 replicas for regional instances.yes infoReplicated MapSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationone or two-phase-commit; repeatable reads; read commitedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlfine grained access rights according to SQL-standard

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More resources
CitusGoogle Cloud SpannerHazelcastLinter
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