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DBMS > Google Cloud Bigtable vs. GridDB vs. Microsoft Azure Data Explorer vs. SiriDB vs. XTDB

System Properties Comparison Google Cloud Bigtable vs. GridDB vs. Microsoft Azure Data Explorer vs. SiriDB vs. XTDB

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSiriDB  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable in-memory time series database optimized for IoT and Big DataFully managed big data interactive analytics platformOpen Source Time Series DBMSA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelKey-value store
Wide column store
Time Series DBMSRelational DBMS infocolumn orientedTime Series DBMSDocument store
Secondary database modelsKey-value store
Relational DBMS
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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websitecloud.google.com/­bigtablegriddb.netazure.microsoft.com/­services/­data-explorersiridb.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.siridb.comwww.xtdb.com/­docs
DeveloperGoogleToshiba CorporationMicrosoftCesbitJuxt Ltd.
Initial release20152013201920172019
Current release5.1, August 2022cloud service with continuous releases1.19, September 2021
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoMIT LicenseOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CClojure
Server operating systemshostedLinuxhostedLinuxAll OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yesschema-free
Typing infopredefined data types such as float or datenoyes 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-typesyes infoNumeric datayes, extensible-data-notation format
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.nonoyesnono
Secondary indexesnoyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)Kusto Query Language (KQL), SQL subsetnolimited SQL, making use of Apache Calcite
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP APIHTTP REST
JDBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Clojure
Java
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Rnono
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID at container levelnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users can be defined per databaseAzure Active Directory Authenticationsimple rights management via user accounts
More information provided by the system vendor
Google Cloud BigtableGridDBMicrosoft Azure Data ExplorerSiriDBXTDB infoformerly named Crux
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Google Cloud BigtableGridDBMicrosoft Azure Data ExplorerSiriDBXTDB infoformerly named Crux
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