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DBMS > Apache Phoenix vs. Cubrid vs. LMDB vs. Spark SQL vs. Splice Machine

System Properties Comparison Apache Phoenix vs. Cubrid vs. LMDB vs. Spark SQL vs. Splice Machine

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCubrid  Xexclude from comparisonLMDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  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 high performant, light-weight, embedded key-value database librarySpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score1.04
Rank#187  Overall
#87  Relational DBMS
Score2.09
Rank#121  Overall
#20  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitephoenix.apache.orgcubrid.com (korean)
cubrid.org (english)
www.symas.com/­symas-embedded-database-lmdbspark.apache.org/­sqlsplicemachine.com
Technical documentationphoenix.apache.orgcubrid.org/­manualswww.lmdb.tech/­docspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperApache Software FoundationCUBRID Corporation, CUBRID FoundationSymasApache Software FoundationSplice Machine
Initial release20142008201120142014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 201911.0, January 20210.9.32, January 20243.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++, JavaCScalaJava
Server operating systemsLinux
Unix
Windows
Linux
Windows
Linux
Unix
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesnonoyes
SQL infoSupport of SQLyesyesnoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsJava Stored Proceduresnonoyes infoJava
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesnoyes
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-standardnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache PhoenixCubridLMDBSpark SQLSplice Machine
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