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DBMS > GBase vs. Hazelcast vs. Informix vs. jBASE vs. Microsoft Azure Data Explorer

System Properties Comparison GBase vs. Hazelcast vs. Informix vs. jBASE vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonHazelcast  Xexclude from comparisonInformix  Xexclude from comparisonjBASE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.A widely adopted in-memory data gridA secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataA robust multi-value DBMS comprising development tools and middlewareFully managed big data interactive analytics platform
Primary database modelRelational DBMSKey-value storeRelational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBMultivalue DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
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
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score17.87
Rank#35  Overall
#22  Relational DBMS
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.gbase.cnhazelcast.comwww.ibm.com/­products/­informixwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbaseazure.microsoft.com/­services/­data-explorer
Technical documentationhazelcast.org/­imdg/­docsinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
docs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperGeneral Data Technology Co., Ltd.HazelcastIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.Rocket Software (formerly Zumasys)Microsoft
Initial release20042008198419912019
Current releaseGBase 8a, GBase 8s, GBase 8c5.3.6, November 202314.10.FC5, November 20205.7cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition 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 languageC, Java, PythonJavaC, C++ and Java
Server operating systemsLinuxAll OS with a Java VMAIX
HP-UX
Linux
macOS
Solaris
Windows
AIX
Linux
Windows
hosted
Data schemeyesschema-freeyesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyes infoSince Version 12.10 support for JSON/BSON datatypesoptionalyes 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.yesyes infothe object must implement a serialization strategyyesyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLStandard with numerous extensionsSQL-like query languageyesEmbedded SQL for jBASE in BASICKusto Query Language (KQL), SQL subset
APIs and other access methodsADO.NET
C API
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Basic
Jabbascript
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor ServicesyesyesYes, possible languages: KQL, Python, R
Triggersyesyes infoEventsyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated MapMulti-source replication
Source-replica replication
yesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACIDACIDno
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.yesyesyesno
User concepts infoAccess controlyesRole-based access controlUsers with fine-grained authentication, authorization, and auditing controlsAccess rights can be defined down to the item levelAzure Active Directory Authentication

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GBaseHazelcastInformixjBASEMicrosoft Azure Data Explorer
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