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

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

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSadas Engine  Xexclude from comparisonSiriDB  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 platformSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen Source Time Series DBMS
Primary database modelKey-value store
Wide column store
Time Series DBMSRelational DBMS infocolumn orientedRelational DBMSTime Series DBMS
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
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score0.03
Rank#379  Overall
#156  Relational DBMS
Score0.11
Rank#346  Overall
#32  Time Series DBMS
Websitecloud.google.com/­bigtablegriddb.netazure.microsoft.com/­services/­data-explorerwww.sadasengine.comsiridb.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.griddb.netdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.siridb.com
DeveloperGoogleToshiba CorporationMicrosoftSADAS s.r.l.Cesbit
Initial release20152013201920062017
Current release5.1, August 2022cloud service with continuous releases8.0
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercial infofree trial version availableOpen 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++C++C
Server operating systemshostedLinuxhostedAIX
Linux
Windows
Linux
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yesyes
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-typesyesyes infoNumeric data
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 subsetyesno
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
JDBC
ODBC
Proprietary protocol
HTTP API
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
.Net
C
C#
C++
Groovy
Java
PHP
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
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 servicehorizontal partitioningSharding
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.noneyes
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
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACID at container levelnono
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.noyesnoyes infomanaged by 'Learn by Usage'yes
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 AuthenticationAccess rights for users, groups and roles according to SQL-standardsimple rights management via user accounts
More information provided by the system vendor
Google Cloud BigtableGridDBMicrosoft Azure Data ExplorerSadas EngineSiriDB
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 ExplorerSadas EngineSiriDB
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