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DBMS > Apache Phoenix vs. Hive vs. LMDB vs. Spark SQL

System Properties Comparison Apache Phoenix vs. Hive vs. LMDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHive  Xexclude from comparisonLMDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBasedata warehouse software for querying and managing large distributed datasets, built on HadoopA high performant, light-weight, embedded key-value database librarySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational 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
Score2.33
Rank#118  Overall
#21  Key-value stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orghive.apache.orgwww.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sql
Technical documentationphoenix.apache.orgcwiki.apache.org/­confluence/­display/­Hive/­Homewww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationApache Software Foundation infoinitially developed by FacebookSymasApache Software Foundation
Initial release2014201220112014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.1.3, April 20220.9.32, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2Open SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaCScala
Server operating systemsLinux
Unix
Windows
All OS with a Java VMLinux
Unix
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesnono
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infouser defined functions and integration of map-reducenono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factornonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
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.yesyesno
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 rolesnono

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Apache PhoenixHiveLMDBSpark SQL
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