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DBMS > Apache Phoenix vs. Riak KV vs. Spark SQL vs. VoltDB

System Properties Comparison Apache Phoenix vs. Riak KV vs. Spark SQL vs. VoltDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonRiak KV  Xexclude from comparisonSpark SQL  Xexclude from comparisonVoltDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDistributed, fault tolerant key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelRelational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#130  Overall
#63  Relational DBMS
Score4.44
Rank#80  Overall
#9  Key-value stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score1.46
Rank#159  Overall
#74  Relational DBMS
Websitephoenix.apache.orgspark.apache.org/­sqlwww.voltdb.com
Technical documentationphoenix.apache.orgwww.tiot.jp/­riak-docs/­riak/­kv/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.voltdb.com
DeveloperApache Software FoundationOpenSource, formerly Basho TechnologiesApache Software FoundationVoltDB Inc.
Initial release2014200920142010
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.2.0, December 20223.5.0 ( 2.13), September 202311.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaErlangScalaJava, C++
Server operating systemsLinux
Unix
Windows
Linux
OS X
Linux
OS X
Windows
Linux
OS X infofor development
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesyesrestrictednoyes
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsyes infoonly a subset of SQL 99
APIs and other access methodsJDBCHTTP API
Native Erlang Interface
JDBC
ODBC
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Java
Python
R
Scala
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsErlangnoJava
Triggersnoyes infopre-commit hooks and post-commit hooksnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"yes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
selectable replication factornoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynono infolinks between data sets can be storednono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyyes, using Riak SecuritynoUsers and roles with access to stored procedures

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Apache PhoenixRiak KVSpark SQLVoltDB
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