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DBMS > Apache Phoenix vs. Hive vs. Lovefield vs. Sphinx vs. Yanza

System Properties Comparison Apache Phoenix vs. Hive vs. Lovefield vs. Sphinx vs. Yanza

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHive  Xexclude from comparisonLovefield  Xexclude from comparisonSphinx  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBasedata warehouse software for querying and managing large distributed datasets, built on HadoopEmbeddable relational database for web apps written in pure JavaScriptOpen source search engine for searching in data from different sources, e.g. relational databasesTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engineTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score0.32
Rank#290  Overall
#132  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websitephoenix.apache.orghive.apache.orggoogle.github.io/­lovefieldsphinxsearch.comyanza.com
Technical documentationphoenix.apache.orgcwiki.apache.org/­confluence/­display/­Hive/­Homegithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsphinxsearch.com/­docs
DeveloperApache Software FoundationApache Software Foundation infoinitially developed by FacebookGoogleSphinx Technologies Inc.Yanza
Initial release20142012201420012015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.1.3, April 20222.1.12, February 20173.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoApache 2.0Open Source infoGPL version 2, commercial licence availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJavaScriptC++
Server operating systemsLinux
Unix
Windows
All OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesnono
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 infofull-text index on all search fieldsno
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like query language infovia JavaScript builder patternSQL-like query language (SphinxQL)no
APIs and other access methodsJDBCJDBC
ODBC
Thrift
Proprietary protocolHTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
JavaScriptC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reducenonono
TriggersnonoUsing read-only observersnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factornonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infousing MemoryDB
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and rolesnonono

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More resources
Apache PhoenixHiveLovefieldSphinxYanza
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