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

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

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Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A 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.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSWide column storeRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#163  Overall
#80  Relational DBMS
Score3.63
Rank#91  Overall
#8  Wide column stores
Score3.41
Rank#93  Overall
#49  Relational DBMS
Score8.01
Rank#56  Overall
#6  Search engines
Websitecubrid.com (korean)
cubrid.org (english)
cloud.google.com/­bigtablecloud.google.com/­spannersphinxsearch.com
Technical documentationcubrid.org/­manualscloud.google.com/­bigtable/­docscloud.google.com/­spanner/­docssphinxsearch.com/­docs
DeveloperCUBRID Corporation, CUBRID FoundationGoogleGoogleSphinx Technologies Inc.
Initial release2008201520172001
Current release11.0, January 20213.4.1, July 2021
License infoCommercial or Open SourceOpen Source infoGPLv2commercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++, JavaC++
Server operating systemsLinux
Windows
hostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesno
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 indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesnoyes infoQuery statements complying to ANSI 2011SQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Proprietary protocol
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresJava Stored Proceduresnonono
Triggersyesnonono
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 replicationInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication with 3 replicas for regional instances.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infoStrict serializable isolationno
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.nonono
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)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
CubridGoogle Cloud BigtableGoogle Cloud SpannerSphinx
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