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DBMS > Microsoft Azure Data Explorer vs. OpenQM vs. Oracle vs. Sphinx vs. TypeDB

System Properties Comparison Microsoft Azure Data Explorer vs. OpenQM vs. Oracle vs. Sphinx vs. TypeDB

Editorial information provided by DB-Engines
NameMicrosoft Azure Data Explorer  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonOracle  Xexclude from comparisonSphinx  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
DescriptionFully managed big data interactive analytics platformQpenQM is a high-performance, self-tuning, multi-value DBMSWidely used RDBMSOpen source search engine for searching in data from different sources, e.g. relational databasesTypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language
Primary database modelRelational DBMS infocolumn orientedMultivalue DBMSRelational DBMSSearch engineGraph DBMS
Relational DBMS infoOften described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.
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
Graph DBMS infowith Oracle Spatial and Graph
RDF store infowith Oracle Spatial and Graph
Spatial DBMS infowith Oracle Spatial and Graph
Vector DBMS infosince Oracle 23
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.34
Rank#284  Overall
#10  Multivalue DBMS
Score1244.08
Rank#1  Overall
#1  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.70
Rank#230  Overall
#20  Graph DBMS
#106  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorerwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmwww.oracle.com/­databasesphinxsearch.comtypedb.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­en/­databasesphinxsearch.com/­docstypedb.com/­docs
DeveloperMicrosoftRocket Software, originally Martin PhillipsOracleSphinx Technologies Inc.Vaticle
Initial release20191993198020012016
Current releasecloud service with continuous releases3.4-1223c, September 20233.5.1, February 20232.26.3, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoGPLv2, extended commercial license availablecommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPL Version 3, commercial licenses 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.
Implementation languageC and C++C++Java
Server operating systemshostedAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeFixed schema with schema-less datatypes (dynamic)yes infowith some exceptionsyes infoSchemaless in JSON and XML columnsyesyes
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-typesyesnoyes
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.yesyesyesno
Secondary indexesall fields are automatically indexedyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLKusto Query Language (KQL), SQL subsetnoyes infowith proprietary extensionsSQL-like query language (SphinxQL)no
APIs and other access methodsMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary protocolgRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Basic
C
Java
Objective C
PHP
Python
C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresYes, possible languages: KQL, Python, RyesPL/SQL infoalso stored procedures in Java possiblenono
Triggersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceyesSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoby using Cassandra
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesMulti-source replication
Source-replica replication
noneMulti-source replication infoby using Cassandra
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono infocan be realized in PL/SQLnoyes infoby using Apache Kafka and Apache Zookeeper
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoisolation level can be parameterizednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoVersion 12c introduced the new option 'Oracle Database In-Memory'no
User concepts infoAccess controlAzure Active Directory AuthenticationAccess rights can be defined down to the item levelfine grained access rights according to SQL-standardnoyes infoat REST API level; other APIs in progress
More information provided by the system vendor
Microsoft Azure Data ExplorerOpenQM infoalso called QMOracleSphinxTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
Microsoft Azure Data ExplorerOpenQM infoalso called QMOracleSphinxTypeDB infoformerly named Grakn
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Conferences, events and webinars

Oracle Cloud World
Las Vegas, 9-12 September 2024

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