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DBMS > Cubrid vs. Google Cloud Spanner vs. SingleStore vs. Splice Machine

System Properties Comparison Cubrid vs. Google Cloud Spanner vs. SingleStore vs. Splice Machine

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Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPA 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.MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#189  Overall
#86  Relational DBMS
Score2.69
Rank#101  Overall
#51  Relational DBMS
Score4.02
Rank#74  Overall
#39  Relational DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitecubrid.com (korean)
cubrid.org (english)
cloud.google.com/­spannerwww.singlestore.comsplicemachine.com
Technical documentationcubrid.org/­manualscloud.google.com/­spanner/­docsdocs.singlestore.comsplicemachine.com/­how-it-works
DeveloperCUBRID Corporation, CUBRID FoundationGoogleSingleStore Inc.Splice Machine
Initial release2008201720132014
Current release11.0, January 20218.5, January 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree developer edition availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaC++, GoJava
Server operating systemsLinux
Windows
hostedLinux info64 bit version requiredLinux
OS X
Solaris
Windows
Data schemeyesyesyesyes
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesyes infoQuery statements complying to ANSI 2011yes infobut no triggers and foreign keysyes
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
Bash
C
C#
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresnoyesyes infoJava
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infohash partitioningShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication with 3 replicas for regional instances.Source-replica replication infostores two copies of each physical data partition on two separate nodesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno infocan define user-defined aggregate functions for map-reduce-style calculationsYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate 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 isolationACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
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)Fine grained access control via users, groups and rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
CubridGoogle Cloud SpannerSingleStore infoformer name was MemSQLSplice Machine
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