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DBMS > Dragonfly vs. HBase vs. jBASE vs. Microsoft Access vs. Microsoft Azure Data Explorer

System Properties Comparison Dragonfly vs. HBase vs. jBASE vs. Microsoft Access vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameDragonfly  Xexclude from comparisonHBase  Xexclude from comparisonjBASE  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceWide-column store based on Apache Hadoop and on concepts of BigTableA robust multi-value DBMS comprising development tools and middlewareMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Fully managed big data interactive analytics platform
Primary database modelKey-value storeWide column storeMultivalue DBMSRelational DBMSRelational DBMS infocolumn oriented
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.49
Rank#261  Overall
#38  Key-value stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitegithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
hbase.apache.orgwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbasewww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­services/­data-explorer
Technical documentationwww.dragonflydb.io/­docshbase.apache.org/­book.htmldocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9developer.microsoft.com/­en-us/­accessdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDragonflyDB team and community contributorsApache Software Foundation infoApache top-level project, originally developed by PowersetRocket Software (formerly Zumasys)MicrosoftMicrosoft
Initial release20232008199119922019
Current release1.0, March 20232.3.4, January 20215.71902 (16.0.11328.20222), March 2019cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoBSL 1.1Open Source infoApache version 2commercialcommercial infoBundled with Microsoft Officecommercial
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 languageC++JavaC++
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
AIX
Linux
Windows
Windows infoNot a real database server, but making use of DLLshosted
Data schemescheme-freeschema-free, schema definition possibleschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or datestrings, hashes, lists, sets, sorted sets, bit arraysoptions to bring your own types, AVROoptionalyesyes 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 indexesnonoyesall fields are automatically indexed
SQL infoSupport of SQLnonoEmbedded SQL for jBASE in BASICyes infobut not compliant to any SQL standardKusto Query Language (KQL), SQL subset
APIs and other access methodsProprietary protocol infoRESP - REdis Serialization ProtocolJava API
RESTful HTTP API
Thrift
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
ADO.NET
DAO
ODBC
OLE DB
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
Basic
Jabbascript
Java
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresLuayes infoCoprocessors in Javayesyes infosince Access 2010 using the ACE-engineYes, possible languages: KQL, Python, R
Triggerspublish/subscribe channels provide some trigger functionalityyesyesyes infosince Access 2010 using the ACE-engineyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
yesnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of command blocks and scriptsSingle row ACID (across millions of columns)ACIDACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayes, strict serializability by the serveryesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlPassword-based authenticationAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights can be defined down to the item levelno infoa simple user-level security was built in till version Access 2003Azure Active Directory Authentication

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More resources
DragonflyHBasejBASEMicrosoft AccessMicrosoft Azure Data Explorer
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