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DBMS > GBase vs. GridDB vs. Hazelcast vs. InterSystems Caché vs. Microsoft Azure Data Explorer

System Properties Comparison GBase vs. GridDB vs. Hazelcast vs. InterSystems Caché vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonGridDB  Xexclude from comparisonHazelcast  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Scalable in-memory time series database optimized for IoT and Big DataA widely adopted in-memory data gridA multi-model DBMS and application serverFully managed big data interactive analytics platform
Primary database modelRelational DBMSTime Series DBMSKey-value storeKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMS infocolumn oriented
Secondary database modelsKey-value store
Relational DBMS
Document store infoJSON support with IMDG 3.12Document storeDocument 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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.gbase.cngriddb.nethazelcast.comwww.intersystems.com/­products/­cacheazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.griddb.nethazelcast.org/­imdg/­docsdocs.intersystems.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperGeneral Data Technology Co., Ltd.Toshiba CorporationHazelcastInterSystemsMicrosoft
Initial release20042013200819972019
Current releaseGBase 8a, GBase 8s, GBase 8c5.1, August 20225.3.6, November 20232018.1.4, May 2020cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2; commercial licenses 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, PythonC++Java
Server operating systemsLinuxLinuxAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
hosted
Data schemeyesyesschema-freedepending on used data modelFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes 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.yesnoyes infothe object must implement a serialization strategyyesyes
Secondary indexesyesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLStandard with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageyesKusto Query Language (KQL), SQL subset
APIs and other access methodsADO.NET
C API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
C++
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresuser defined functionsnoyes infoEvent Listeners, Executor ServicesyesYes, possible languages: KQL, Python, R
Triggersyesyesyes infoEventsyesyes 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 partitioningShardingShardingnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoReplicated MapSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelone or two-phase-commit; repeatable reads; read commitedACIDno
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 controlyesAccess rights for users can be defined per databaseRole-based access controlAccess rights for users, groups and rolesAzure Active Directory Authentication
More information provided by the system vendor
GBaseGridDBHazelcastInterSystems CachéMicrosoft Azure Data Explorer
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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GBaseGridDBHazelcastInterSystems CachéMicrosoft Azure Data Explorer
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