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DBMS > Google Cloud Bigtable vs. Informix vs. Microsoft Azure Data Explorer vs. ObjectBox

System Properties Comparison Google Cloud Bigtable vs. Informix vs. Microsoft Azure Data Explorer vs. ObjectBox

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonInformix  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonObjectBox  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.A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things dataFully managed big data interactive analytics platformLightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors
Primary database modelKey-value store
Wide column store
Relational DBMS infoSince Version 12.10 support for JSON/BSON datatypes compatible with MongoDBRelational DBMS infocolumn orientedObject oriented DBMS
Vector DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS infowith Informix TimeSeries Extension
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
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score16.32
Rank#35  Overall
#21  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score1.08
Rank#179  Overall
#6  Object oriented DBMS
#9  Vector DBMS
Websitecloud.google.com/­bigtablewww.ibm.com/­products/­informixazure.microsoft.com/­services/­data-explorergithub.com/­objectbox
objectbox.io
Technical documentationcloud.google.com/­bigtable/­docsinformix.hcldoc.com
www.ibm.com/­support/­knowledgecenter/­SSGU8G/­welcomeIfxServers.html
docs.microsoft.com/­en-us/­azure/­data-explorerdocs.objectbox.io
DeveloperGoogleIBM, HCL Technologies infoEffective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.MicrosoftObjectBox Limited
Initial release2015198420192017
Current release14.10.FC5, November 2020cloud service with continuous releases4.0 (May 2024)
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availablecommercialBindings are released under Apache 2.0 infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and JavaC and C++
Server operating systemshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedAndroid
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or datenoyes infoSince Version 12.10 support for JSON/BSON datatypesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes, plus "flex" map-like 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.noyesno
Secondary indexesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLnoyesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
JSON API infoMongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary native API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, Rno
Triggersnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Data sync between devices allowing occasional connected databases to work completely offline
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authentication, authorization, and auditing controlsAzure Active Directory Authenticationyes
More information provided by the system vendor
Google Cloud BigtableInformixMicrosoft Azure Data ExplorerObjectBox
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More resources
Google Cloud BigtableInformixMicrosoft Azure Data ExplorerObjectBox
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