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DBMS > Apache Phoenix vs. Cubrid vs. Google Cloud Spanner vs. Solr

System Properties Comparison Apache Phoenix vs. Cubrid vs. Google Cloud Spanner vs. Solr

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCubrid  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseCUBRID 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.A widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitephoenix.apache.orgcubrid.com (korean)
cubrid.org (english)
cloud.google.com/­spannersolr.apache.org
Technical documentationphoenix.apache.orgcubrid.org/­manualscloud.google.com/­spanner/­docssolr.apache.org/­resources.html
DeveloperApache Software FoundationCUBRID Corporation, CUBRID FoundationGoogleApache Software Foundation
Initial release2014200820172006
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201911.0, January 20219.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++, JavaJava
Server operating systemsLinux
Unix
Windows
Linux
Windows
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.nononoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesyesyes infoQuery statements complying to ANSI 2011Solr Parallel SQL Interface
APIs and other access methodsJDBCADO.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
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsJava Stored ProceduresnoJava plugins
Triggersnoyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationMulti-source replication with 3 replicas for regional instances.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes infousing Google Cloud Dataflowspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyes 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 dataACIDACIDACID infoStrict serializable isolationoptimistic locking
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.yesnonoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes

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Apache PhoenixCubridGoogle Cloud SpannerSolr
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