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DBMS > Apache Druid vs. OushuDB vs. Quasardb vs. Splice Machine

System Properties Comparison Apache Druid vs. OushuDB vs. Quasardb vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonOushuDB  Xexclude from comparisonQuasardb  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learningDistributed, high-performance timeseries databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score0.10
Rank#355  Overall
#154  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitedruid.apache.orgwww.oushu.com/­product/­oushuDBquasar.aisplicemachine.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.oushu.com/­documentationdoc.quasar.ai/­mastersplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsOushuquasardbSplice Machine
Initial release201220092014
Current release29.0.1, April 20244.0.1, August 20203.14.1, January 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemsLinux
OS X
Unix
LinuxBSD
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryyes
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.nono
Secondary indexesyesyesyes infowith tagsyes
SQL infoSupport of SQLSQL for queryingFull-featured ANSI SQL supportSQL-like query languageyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C++
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnoyes infoJava
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedyesSharding infoconsistent hashingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replication with selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationwith Hadoop integrationYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoTransient modeyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemKerberos, SSL and role based accessCryptographically strong user authentication and audit trailAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache DruidOushuDBQuasardbSplice Machine
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