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DBMS > Datomic vs. GridDB vs. InterSystems Caché vs. jBASE vs. Microsoft Azure Data Explorer

System Properties Comparison Datomic vs. GridDB vs. InterSystems Caché vs. jBASE vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGridDB  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonjBASE  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.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityScalable in-memory time series database optimized for IoT and Big DataA multi-model DBMS and application serverA robust multi-value DBMS comprising development tools and middlewareFully managed big data interactive analytics platform
Primary database modelRelational DBMSTime Series DBMSKey-value store
Object oriented DBMS
Relational DBMS
Multivalue DBMSRelational DBMS infocolumn oriented
Secondary database modelsKey-value store
Relational DBMS
Document 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
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score1.49
Rank#156  Overall
#3  Multivalue DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitewww.datomic.comgriddb.netwww.intersystems.com/­products/­cachewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbaseazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.datomic.comdocs.griddb.netdocs.intersystems.comdocs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperCognitectToshiba CorporationInterSystemsRocket Software (formerly Zumasys)Microsoft
Initial release20122013199719912019
Current release1.0.7075, December 20235.1, August 20222018.1.4, May 20205.7cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercialcommercial
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 languageJava, ClojureC++
Server operating systemsAll OS with a Java VMLinuxAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
AIX
Linux
Windows
hosted
Data schemeyesyesdepending on used data modelschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesoptionalyes 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.nonoyesyesyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yesEmbedded SQL for jBASE in BASICKusto Query Language (KQL), SQL subset
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
.NET Client API
JDBC
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 languagesClojure
Java
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
.Net
Basic
Jabbascript
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoyesyesYes, possible languages: KQL, Python, R
TriggersBy using transaction functionsyesyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingnoneShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationSource-replica replicationyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonoSpark 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 ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesyesyesno
User concepts infoAccess controlnoAccess rights for users can be defined per databaseAccess rights for users, groups and rolesAccess rights can be defined down to the item levelAzure Active Directory Authentication
More information provided by the system vendor
DatomicGridDBInterSystems CachéjBASEMicrosoft 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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DatomicGridDBInterSystems CachéjBASEMicrosoft Azure Data Explorer
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