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

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

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonLMDB  Xexclude from comparisonRealm  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA high performant, light-weight, embedded key-value database libraryA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score2.33
Rank#118  Overall
#21  Key-value stores
Score7.71
Rank#52  Overall
#9  Document stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitephoenix.apache.orgwww.symas.com/­symas-embedded-database-lmdbrealm.iospark.apache.org/­sql
Technical documentationphoenix.apache.orgwww.lmdb.tech/­docrealm.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationSymasRealm, acquired by MongoDB in May 2019Apache Software Foundation
Initial release2014201120142014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.9.32, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen 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 languageJavaCScala
Server operating systemsLinux
Unix
Windows
Linux
Unix
Windows
Android
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes
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.nononono
Secondary indexesyesnoyesno
SQL infoSupport of SQLyesnonoSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.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
.Net
Java infowith Android only
Objective-C
React Native
Swift
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnono inforuns within the applications so server-side scripts are unnecessaryno
Triggersnonoyes infoChange Listenersno
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
nonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 infoIn-Memory realmno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoyesno

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Apache PhoenixLMDBRealmSpark SQL
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