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DBMS > Google Cloud Datastore vs. GridDB vs. Microsoft Azure Table Storage vs. XTDB

System Properties Comparison Google Cloud Datastore vs. GridDB vs. Microsoft Azure Table Storage vs. XTDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGridDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformScalable in-memory time series database optimized for IoT and Big DataA Wide Column Store for rapid development using massive semi-structured datasetsA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelDocument storeTime Series DBMSWide column storeDocument store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.11
Rank#343  Overall
#46  Document stores
Websitecloud.google.com/­datastoregriddb.netazure.microsoft.com/­en-us/­services/­storage/­tablesgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationcloud.google.com/­datastore/­docsdocs.griddb.netwww.xtdb.com/­docs
DeveloperGoogleToshiba CorporationMicrosoftJuxt Ltd.
Initial release2008201320122019
Current release5.1, August 20221.19, 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 License
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++Clojure
Server operating systemshostedLinuxhostedAll OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details hereyes infonumerical, string, blob, geometry, boolean, timestampyesyes, 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.nononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL92, SQL-like TQL (Toshiba Query Language)nolimited SQL, making use of Apache Calcite
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP APIHTTP REST
JDBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Server-side scripts infoStored proceduresusing Google App Enginenonono
TriggersCallbacks using the Google Apps Engineyesnono
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 nodesMulti-source replication using PaxosSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflowConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID at container leveloptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, 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.noyesno
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 databaseAccess rights based on private key authentication or shared access signatures
More information provided by the system vendor
Google Cloud DatastoreGridDBMicrosoft Azure Table StorageXTDB 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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More resources
Google Cloud DatastoreGridDBMicrosoft Azure Table StorageXTDB infoformerly named Crux
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