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

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

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionWidely 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 databasesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value storeRelational DBMS infocolumn orientedSearch engineTime Series DBMS
Secondary database modelsDocument 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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.gbase.cnhazelcast.comazure.microsoft.com/­services/­data-explorersphinxsearch.comwww.timescale.com
Technical documentationhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docsdocs.timescale.com
DeveloperGeneral Data Technology Co., Ltd.HazelcastMicrosoftSphinx Technologies Inc.Timescale
Initial release20042008201920012017
Current releaseGBase 8a, GBase 8s, GBase 8c5.3.6, November 2023cloud service with continuous releases3.5.1, February 20232.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, PythonJavaC++C
Server operating systemsLinuxAll OS with a Java VMhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yesyes
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-typesnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex 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.yesyes infothe object must implement a serialization strategyyesyes
Secondary indexesyesyesall fields are automatically indexedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLStandard with numerous extensionsSQL-like query languageKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)yes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
C API
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#.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
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Rnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal 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 supportedyes, across time and space (hash partitioning) attributes
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.noneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlyesRole-based access controlAzure Active Directory Authenticationnofine grained access rights according to SQL-standard

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More resources
GBaseHazelcastMicrosoft Azure Data ExplorerSphinxTimescaleDB
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