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DBMS > Apache Druid vs. HBase vs. Quasardb vs. Stardog

System Properties Comparison Apache Druid vs. HBase vs. Quasardb vs. Stardog

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHBase  Xexclude from comparisonQuasardb  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataWide-column store based on Apache Hadoop and on concepts of BigTableDistributed, high-performance timeseries databaseEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMS
Time Series DBMS
Wide column storeTime Series DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score0.19
Rank#327  Overall
#30  Time Series DBMS
Score2.05
Rank#129  Overall
#11  Graph DBMS
#6  RDF stores
Websitedruid.apache.orghbase.apache.orgquasar.aiwww.stardog.com
Technical documentationdruid.apache.org/­docs/­latest/­designhbase.apache.org/­book.htmldoc.quasar.ai/­masterdocs.stardog.com
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by PowersetquasardbStardog-Union
Initial release2012200820092010
Current release29.0.1, April 20242.3.4, January 20213.14.1, January 20247.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache version 2commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++Java
Server operating systemsLinux
OS X
Unix
Linux
Unix
Windows infousing Cygwin
BSD
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeyes infoschema-less columns are supportedschema-free, schema definition possibleschema-freeschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyes 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.nononono infoImport/export of XML data possible
Secondary indexesyesnoyes infowith tagsyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL for queryingnoSQL-like query languageYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
HTTP APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javanouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyesnoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoconsistent hashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
Source-replica replication with selectable replication factorMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyeswith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoSingle row ACID (across millions of columns)ACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesyes infoTransient modeyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACCryptographically strong user authentication and audit trailAccess rights for users and roles

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More resources
Apache DruidHBaseQuasardbStardog
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