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DBMS > Apache Druid vs. Splice Machine vs. Virtuoso

System Properties Comparison Apache Druid vs. Splice Machine vs. Virtuoso

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonSplice Machine  Xexclude from comparisonVirtuoso  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkVirtuoso is a multi-model hybrid-RDBMS that supports management of data represented as relational tables and/or property graphs
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.69
Rank#103  Overall
#51  Relational DBMS
#7  Time Series DBMS
Score0.71
Rank#201  Overall
#101  Relational DBMS
Score2.88
Rank#99  Overall
#19  Document stores
#5  Graph DBMS
#3  Native XML DBMS
#50  Relational DBMS
#3  RDF stores
#9  Search engines
Websitedruid.apache.orgsplicemachine.comvirtuoso.openlinksw.com
Technical documentationdruid.apache.org/­docs/­latest/­designdoc.splicemachine.comdocs.openlinksw.com/­virtuoso
DeveloperApache Software Foundation and contributorsSplice MachineOpenLink Software
Initial release201220141998
Current release0.20.1, January 20212.008.03.3316, March 2020
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoAGPL 3.0, commercial license availableOpen Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
Windows
AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyes infoSQL - Standard relational schema
RDF - Quad (S, P, O, G) or Triple (S, P, O)
XML - DTD, XML Schema
DAV - freeform filesystem objects, plus User Defined Types a/k/a Dynamic Extension Type
Typing infopredefined data types such as float or dateyesyesyes
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.noyes
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL for queryingyesyes infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
ADO.NET
GeoSPARQL
HTTP API
JDBC
Jena RDF API
ODBC
OLE DB
RDF4J API
RESTful HTTP API
Sesame REST HTTP Protocol
SOAP webservices
SPARQL 1.1
WebDAV
XPath
XQuery
XSLT
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
C
C#
C++
Java
JavaScript
Perl
PHP
Python
Ruby
Visual Basic
Server-side scripts infoStored proceduresnoyes infoJavayes infoVirtuoso PL
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShared Nothhing Auto-Sharding, Columnar Partitioningyes
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication
Source-replica replication
Chain, star, and bi-directional replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles according to SQL-standardFine-grained Attribute-Based Access Control (ABAC) in addition to typical coarse-grained Role-Based Access Control (RBAC) according to SQL-standard. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
Apache DruidSplice MachineVirtuoso
Specific characteristicsTHE ONLY SCALE-OUT SQL RDBMS WITH BUILT-IN MACHINE LEARNING For data-rich, real-time...
» more
Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more
Competitive advantagesOperational Workloads: Full ACID support with high performance at scale Multi-row...
» more
Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more
Typical application scenariosNew AI/ML and IoT Applications Data Warehouse Offloads Application Modernization...
» more
Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more
Key customersBroad use across enterprises and governments including — European Union (EU) US Government...
» more
Market metricsLargest installed-base ​of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more
Licensing and pricing modelsKubernetes Community Edition: https://hub.helm.sh/charts/splicemachine/splice-helm...
» more
Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
» more
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More resources
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