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DBMS > Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. ObjectBox vs. Stardog

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure Table Storage vs. ObjectBox vs. Stardog

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonObjectBox  Xexclude from comparisonStardog  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 Wide Column Store for rapid development using massive semi-structured datasetsExtremely fast embedded database for small devices, IoT and MobileEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelKey-value store
Wide column store
Wide column storeObject oriented DBMSGraph DBMS
RDF store
Secondary database modelsTime Series DBMS
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
Score4.48
Rank#75  Overall
#6  Wide column stores
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitecloud.google.com/­bigtableazure.microsoft.com/­en-us/­services/­storage/­tablesobjectbox.iowww.stardog.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.objectbox.iodocs.stardog.com
DeveloperGoogleMicrosoftObjectBox LimitedStardog-Union
Initial release2015201220172010
Current release7.3.0, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache License 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++Java
Server operating systemshostedhostedAndroid
iOS
Linux
macOS
Windows
Linux
macOS
Windows
Data schemeschema-freeschema-freeyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or datenoyesyesyes
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.nononono infoImport/export of XML data possible
Secondary indexesnonoyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnononoYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP APIProprietary native APIGraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnononouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnononoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.online/offline synchronization between client and serverMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynonoyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsoptimistic lockingACIDACID
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.nononoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights based on private key authentication or shared access signaturesyesAccess rights for users and roles
More information provided by the system vendor
Google Cloud BigtableMicrosoft Azure Table StorageObjectBoxStardog
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15 February 2024

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14 November 2023

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More resources
Google Cloud BigtableMicrosoft Azure Table StorageObjectBoxStardog
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