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DBMS > IBM Db2 vs. Microsoft Azure Data Explorer vs. NSDb vs. Oracle Berkeley DB vs. PouchDB

System Properties Comparison IBM Db2 vs. Microsoft Azure Data Explorer vs. NSDb vs. Oracle Berkeley DB vs. PouchDB

Editorial information provided by DB-Engines
NameIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNSDb  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionCommon in IBM host environments, 2 different versions for host and Windows/LinuxFully managed big data interactive analytics platformScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesWidely used in-process key-value storeJavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMS infocolumn orientedTime Series DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Document 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score125.90
Rank#9  Overall
#6  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Websitewww.ibm.com/­products/­db2azure.microsoft.com/­services/­data-explorernsdb.iowww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlpouchdb.com
Technical documentationwww.ibm.com/­docs/­en/­db2docs.microsoft.com/­en-us/­azure/­data-explorernsdb.io/­Architecturedocs.oracle.com/­cd/­E17076_05/­html/­index.htmlpouchdb.com/­guides
DeveloperIBMMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software Foundation
Initial release1983 infohost version2019201719942012
Current release12.1, October 2016cloud service with continuous releases18.1.40, May 20207.1.1, June 2019
License infoCommercial or Open Sourcecommercial infofree version is availablecommercialOpen Source infoApache Version 2.0Open Source infocommercial license availableOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++Java, ScalaC, Java, C++ (depending on the Berkeley DB edition)JavaScript
Server operating systemsAIX
HP-UX
Linux
Solaris
Windows
z/OS
hostedLinux
macOS
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesFixed schema with schema-less datatypes (dynamic)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes: int, bigint, decimal, stringnono
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 infoonly with the Berkeley DB XML editionno
Secondary indexesyesall fields are automatically indexedall fields are automatically indexedyesyes infovia views
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetSQL-like query languageyes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
gRPC
HTTP REST
WebSocket
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesC
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Scala
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
JavaScript
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, RnonoView functions in JavaScript
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoonly for the SQL APIyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoonly with Windows/Unix/Linux VersionSharding infoImplicit feature of the cloud serviceShardingnoneSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesyes infowith separate tools (MQ, InfoSphere)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationnono

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More resources
IBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerNSDbOracle Berkeley DBPouchDB
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