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DBMS > GBase vs. GridDB vs. Immudb vs. Microsoft Azure Data Explorer vs. TimescaleDB

System Properties Comparison GBase vs. GridDB vs. Immudb vs. Microsoft Azure Data Explorer vs. TimescaleDB

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonGridDB  Xexclude from comparisonImmudb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTimescaleDB  Xexclude from comparison
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 DataAn open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.Fully managed big data interactive analytics platformA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSTime Series DBMSKey-value storeRelational DBMS infocolumn orientedTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMSDocument 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
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.31
Rank#295  Overall
#42  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitewww.gbase.cngriddb.netgithub.com/­codenotary/­immudb
immudb.io
azure.microsoft.com/­services/­data-explorerwww.timescale.com
Technical documentationdocs.griddb.netdocs.immudb.iodocs.microsoft.com/­en-us/­azure/­data-explorerdocs.timescale.com
DeveloperGeneral Data Technology Co., Ltd.Toshiba CorporationCodenotaryMicrosoftTimescale
Initial release20042013202020192017
Current releaseGBase 8a, GBase 8s, GBase 8c5.1, August 20221.2.3, April 2022cloud service with continuous releases2.15.0, May 2024
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 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, Java, PythonC++GoC
Server operating systemsLinuxLinuxBSD
Linux
macOS
Solaris
Windows
z/OS
hostedLinux
OS X
Windows
Data schemeyesyesschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnumerics, 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.yesnonoyesyes
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLStandard with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like syntaxKusto Query Language (KQL), SQL subsetyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
C API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
gRPC protocol
PostgreSQL wire protocol
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsnonoYes, possible languages: KQL, Python, Ruser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningShardingShardingSharding infoImplicit feature of the cloud serviceyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDnoACID
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.yesnonono
User concepts infoAccess controlyesAccess rights for users can be defined per databaseAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
GBaseGridDBImmudbMicrosoft Azure Data ExplorerTimescaleDB
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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More resources
GBaseGridDBImmudbMicrosoft Azure Data ExplorerTimescaleDB
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