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DBMS > Microsoft Azure Data Explorer vs. SingleStore vs. Sphinx vs. Splice Machine vs. Virtuoso

System Properties Comparison Microsoft Azure Data Explorer vs. SingleStore vs. Sphinx vs. Splice Machine vs. Virtuoso

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonVirtuoso  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-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 infocolumn orientedRelational DBMSSearch engineRelational DBMSDocument store
Graph DBMS
Native XML DBMS
Relational DBMS
RDF store
Search engine
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Document store
Spatial DBMS
Time Series DBMS
Vector DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score5.38
Rank#62  Overall
#35  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score4.27
Rank#73  Overall
#13  Document stores
#4  Graph DBMS
#2  Native XML DBMS
#39  Relational DBMS
#2  RDF stores
#9  Search engines
Websiteazure.microsoft.com/­services/­data-explorerwww.singlestore.comsphinxsearch.comsplicemachine.comvirtuoso.openlinksw.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.singlestore.comsphinxsearch.com/­docssplicemachine.com/­how-it-worksdocs.openlinksw.com/­virtuoso
DeveloperMicrosoftSingleStore Inc.Sphinx Technologies Inc.Splice MachineOpenLink Software
Initial release20192013200120141998
Current releasecloud service with continuous releases8.5, January 20243.5.1, February 20233.1, March 20217.2.11, September 2023
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availableOpen Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageC++, GoC++JavaC
Server operating systemshostedLinux info64 bit version requiredFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
AIX
FreeBSD
HP-UX
Linux
OS X
Solaris
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)yesyesyesyes 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 dateyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesnoyesyes
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.yesnoyes
Secondary indexesall fields are automatically indexedyesyes infofull-text index on all search fieldsyesyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetyes infobut no triggers and foreign keysSQL-like query language (SphinxQL)yesyes infoSQL-92, SQL-200x, SQL-3, SQLX
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Proprietary protocolJDBC
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 languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Bash
C
C#
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
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 proceduresYes, possible languages: KQL, Python, Ryesnoyes infoJavayes infoVirtuoso PL
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infohash partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioningyes
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infostores two copies of each physical data partition on two separate nodesnoneMulti-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 methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocan define user-defined aggregate functions for map-reduce-style calculationsnoYes, via Full Spark Integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlAzure Active Directory AuthenticationFine grained access control via users, groups and rolesnoAccess 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
Microsoft Azure Data ExplorerSingleStore infoformer name was MemSQLSphinxSplice MachineVirtuoso
Specific characteristicsSingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Virtuoso is a modern multi-model RDBMS for managing data represented as tabular relations...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Performance & Scale — as exemplified by DBpedia and the LOD Cloud it spawned, i.e.,...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Used for — Analytics/BI Conceptual Data Virtualization Enterprise Knowledge Graphs...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Broad use across enterprises and governments including — European Union (EU) US Government...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Largest installed-base ​of Multi-Model RDBMS for AI-friendly Knowledge Graphs Platform...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more
Available in both Commercial Enterprise and Open Source (GPL v2) Editions Feature...
» more

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More resources
Microsoft Azure Data ExplorerSingleStore infoformer name was MemSQLSphinxSplice MachineVirtuoso
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