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DBMS > Apache Phoenix vs. DataFS vs. IBM Db2 vs. jBASE vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Phoenix vs. DataFS vs. IBM Db2 vs. jBASE vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDataFS  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonjBASE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.Common in IBM host environments, 2 different versions for host and Windows/LinuxA robust multi-value DBMS comprising development tools and middlewareFully managed big data interactive analytics platform
Primary database modelRelational DBMSObject oriented DBMSRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBMultivalue DBMSRelational DBMS infocolumn oriented
Secondary database modelsGraph DBMSDocument 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
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
Score125.90
Rank#9  Overall
#6  Relational DBMS
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitephoenix.apache.orgnewdatabase.comwww.ibm.com/­products/­db2www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbaseazure.microsoft.com/­services/­data-explorer
Technical documentationphoenix.apache.orgdev.mobiland.com/­Overview.xspwww.ibm.com/­docs/­en/­db2docs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software FoundationMobiland AGIBMRocket Software (formerly Zumasys)Microsoft
Initial release201420181983 infohost version19912019
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.1.263, October 202212.1, October 20165.7cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree version is availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++
Server operating systemsLinux
Unix
Windows
WindowsAIX
HP-UX
Linux
Solaris
Windows
z/OS
AIX
Linux
Windows
hosted
Data schemeyes infolate-bound, schema-on-read capabilitiesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesoptionalyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonoyesyes
Secondary indexesyesnoyesall fields are automatically indexed
SQL infoSupport of SQLyesnoyesEmbedded SQL for jBASE in BASICKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC.NET Client API
Proprietary client DLL
WinRT client
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
VB.Net
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
.Net
Basic
Jabbascript
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsyesyesYes, possible languages: KQL, Python, R
Triggersnono, except callback-events from server when changes happenedyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingProprietary Sharding systemSharding infoonly with Windows/Unix/Linux VersionShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infowith separate tools (MQ, InfoSphere)yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyWindows-Profilefine grained access rights according to SQL-standardAccess rights can be defined down to the item levelAzure Active Directory Authentication

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More resources
Apache PhoenixDataFSIBM Db2 infoformerly named DB2 or IBM Database 2jBASEMicrosoft Azure Data Explorer
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