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DBMS > Apache Druid vs. Riak KV vs. Spark SQL vs. Valentina Server

System Properties Comparison Apache Druid vs. Riak KV vs. Spark SQL vs. Valentina Server

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonRiak KV  Xexclude from comparisonSpark SQL  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDistributed, fault tolerant key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingObject-relational database and reports server
Primary database modelRelational DBMS
Time Series DBMS
Key-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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitedruid.apache.orgspark.apache.org/­sqlwww.valentina-db.net
Technical documentationdruid.apache.org/­docs/­latest/­designwww.tiot.jp/­riak-docs/­riak/­kv/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperApache Software Foundation and contributorsOpenSource, formerly Basho TechnologiesApache Software FoundationParadigma Software
Initial release2012200920141999
Current release29.0.1, April 20243.2.0, December 20223.5.0 ( 2.13), September 20235.7.5
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaErlangScala
Server operating systemsLinux
OS X
Unix
Linux
OS X
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-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 SQLSQL for queryingnoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HTTP API
Native Erlang Interface
JDBC
ODBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
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
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnoErlangnoyes
Triggersnoyes infopre-commit hooks and post-commit hooksnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infono "single point of failure"yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynono infolinks between data sets can be storednoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyes, using Riak Securitynofine grained access rights according to SQL-standard

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More resources
Apache DruidRiak KVSpark SQLValentina Server
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