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DBMS > Cubrid vs. Google Cloud Spanner vs. GridGain vs. Sphinx

System Properties Comparison Cubrid vs. Google Cloud Spanner vs. GridGain vs. Sphinx

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Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonGridGain  Xexclude from comparisonSphinx  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.GridGain is an in-memory computing platform, built on Apache IgniteOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitecubrid.com (korean)
cubrid.org (english)
cloud.google.com/­spannerwww.gridgain.comsphinxsearch.com
Technical documentationcubrid.org/­manualscloud.google.com/­spanner/­docswww.gridgain.com/­docs/­index.htmlsphinxsearch.com/­docs
DeveloperCUBRID Corporation, CUBRID FoundationGoogleGridGain Systems, Inc.Sphinx Technologies Inc.
Initial release2008201720072001
Current release11.0, January 2021GridGain 8.5.13.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoGPL version 2, commercial licence 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++, JavaJava, C++, .NetC++
Server operating systemsLinux
Windows
hostedLinux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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.nonoyes
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesyes infoQuery statements complying to ANSI 2011ANSI-99 for query and DML statements, subset of DDLSQL-like query language (SphinxQL)
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
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresJava Stored Proceduresnoyes (compute grid and cache interceptors can be used instead)no
Triggersyesnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication with 3 replicas for regional instances.yes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
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)Security Hooks for custom implementationsno

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More resources
CubridGoogle Cloud SpannerGridGainSphinx
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