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DBMS > Apache Phoenix vs. H2 vs. MarkLogic vs. Solr

System Properties Comparison Apache Phoenix vs. H2 vs. MarkLogic vs. Solr

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonH2  Xexclude from comparisonMarkLogic  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Operational and transactional Enterprise NoSQL databaseA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Search engine
Secondary database modelsSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score42.91
Rank#24  Overall
#3  Search engines
Websitephoenix.apache.orgwww.h2database.comwww.marklogic.comsolr.apache.org
Technical documentationphoenix.apache.orgwww.h2database.com/­html/­main.htmldocs.marklogic.comsolr.apache.org/­resources.html
DeveloperApache Software FoundationThomas MuellerMarkLogic Corp.Apache Software Foundation
Initial release2014200520012006
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.2.220, July 202311.0, December 20229.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infodual-licence (Mozilla public license, Eclipse public license)commercial inforestricted free version is availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++Java
Server operating systemsLinux
Unix
Windows
All OS with a Java VMLinux
OS X
Windows
All 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 capabilitiesyesschema-free infoSchema can be enforcedyes 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.nonoyesyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesyesyes infoSQL92Solr Parallel SQL Interface
APIs and other access methodsJDBCJDBC
ODBC
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
JavaC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.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 Procedures and User-Defined Functionsyes infovia XQuery or JavaScriptJava plugins
Triggersnoyesyesyes 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
With clustering: 2 database servers on different computers operate on identical copies of a databaseyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsspark-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 integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infocan act as a resource manager in an XA/JTA transactionoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.yesyesyes, with Range Indexesyes
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-standardRole-based access control at the document and subdocument levelsyes

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More resources
Apache PhoenixH2MarkLogicSolr
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