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DBMS > IBM Db2 vs. MarkLogic vs. Microsoft Azure Data Explorer vs. NSDb vs. RavenDB

System Properties Comparison IBM Db2 vs. MarkLogic vs. Microsoft Azure Data Explorer vs. NSDb vs. RavenDB

Editorial information provided by DB-Engines
NameIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNSDb  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionCommon in IBM host environments, 2 different versions for host and Windows/LinuxOperational and transactional Enterprise NoSQL databaseFully managed big data interactive analytics platformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMS infocolumn orientedTime Series DBMSDocument store
Secondary database modelsDocument store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
Document 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
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score125.90
Rank#9  Overall
#6  Relational DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websitewww.ibm.com/­products/­db2www.progress.com/­marklogicazure.microsoft.com/­services/­data-explorernsdb.ioravendb.net
Technical documentationwww.ibm.com/­docs/­en/­db2www.progress.com/­marklogic/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architectureravendb.net/­docs
DeveloperIBMMarkLogic Corp.MicrosoftHibernating Rhinos
Initial release1983 infohost version2001201920172010
Current release12.1, October 201611.0, December 2022cloud service with continuous releases5.4, July 2022
License infoCommercial or Open Sourcecommercial infofree version is availablecommercial inforestricted free version is availablecommercialOpen Source infoApache Version 2.0Open Source infoAGPL version 3, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++Java, ScalaC#
Server operating systemsAIX
HP-UX
Linux
Solaris
Windows
z/OS
Linux
OS X
Windows
hostedLinux
macOS
Linux
macOS
Raspberry Pi
Windows
Data schemeyesschema-free infoSchema can be enforcedFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes: int, bigint, decimal, stringno
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.yesyesno
Secondary indexesyesyesall fields are automatically indexedall fields are automatically indexedyes
SQL infoSupport of SQLyesyes infoSQL92Kusto Query Language (KQL), SQL subsetSQL-like query languageSQL-like query language (RQL)
APIs and other access methodsADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
HTTP REST
WebSocket
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesC
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyes infovia XQuery or JavaScriptYes, possible languages: KQL, Python, Rnoyes
Triggersyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoonly with Windows/Unix/Linux VersionShardingSharding infoImplicit feature of the cloud serviceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infowith separate tools (MQ, InfoSphere)yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infocan act as a resource manager in an XA/JTA transactionnonoACID, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, with Range Indexesno
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access control at the document and subdocument levelsAzure Active Directory AuthenticationAuthorization levels configured per client per database

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More resources
IBM Db2 infoformerly named DB2 or IBM Database 2MarkLogicMicrosoft Azure Data ExplorerNSDbRavenDB
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