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DBMS > DataFS vs. GBase vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Sphinx

System Properties Comparison DataFS vs. GBase vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Sphinx

Editorial information provided by DB-Engines
NameDataFS  Xexclude from comparisonGBase  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAll 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.Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.A widely adopted in-memory data gridFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelObject oriented DBMSRelational DBMSKey-value storeRelational DBMS infocolumn orientedSearch engine
Secondary database modelsGraph DBMSDocument store infoJSON support with IMDG 3.12Document 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
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitenewdatabase.comwww.gbase.cnhazelcast.comazure.microsoft.com/­services/­data-explorersphinxsearch.com
Technical documentationdev.mobiland.com/­Overview.xsphazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docs
DeveloperMobiland AGGeneral Data Technology Co., Ltd.HazelcastMicrosoftSphinx Technologies Inc.
Initial release20182004200820192001
Current release1.1.263, October 2022GBase 8a, GBase 8s, GBase 8c5.3.6, November 2023cloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, PythonJavaC++
Server operating systemsWindowsLinuxAll OS with a Java VMhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeClasses, 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)yes
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.noyesyes infothe object must implement a serialization strategyyes
Secondary indexesnoyesyesall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLnoStandard with numerous extensionsSQL-like query languageKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)
APIs and other access methods.NET Client API
Proprietary client DLL
WinRT client
ADO.NET
C API
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol
Supported programming languages.Net
C
C#
C++
VB.Net
C#.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Rno
Triggersno, except callback-events from server when changes happenedyesyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemhorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlWindows-ProfileyesRole-based access controlAzure Active Directory Authenticationno

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More resources
DataFSGBaseHazelcastMicrosoft Azure Data ExplorerSphinx
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