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DBMS > EXASOL vs. Google Cloud Datastore vs. GridDB vs. IBM Cloudant

System Properties Comparison EXASOL vs. Google Cloud Datastore vs. GridDB vs. IBM Cloudant

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridDB  Xexclude from comparisonIBM Cloudant  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformScalable in-memory time series database optimized for IoT and Big DataDatabase as a Service offering based on Apache CouchDB
Primary database modelRelational DBMSDocument storeTime Series DBMSDocument store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score2.75
Rank#104  Overall
#19  Document stores
Websitewww.exasol.comcloud.google.com/­datastoregriddb.netwww.ibm.com/­products/­cloudant
Technical documentationwww.exasol.com/­resourcescloud.google.com/­datastore/­docsdocs.griddb.netcloud.ibm.com/­docs/­Cloudant
DeveloperExasolGoogleToshiba CorporationIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014
Initial release2000200820132010
Current release5.1, August 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Erlang
Server operating systemshostedLinuxhosted
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyes infonumerical, string, blob, geometry, boolean, timestampno
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 indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methods.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP/JSON API
Supported programming languagesJava
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
JavaScript
Objective-C
PHP
Ruby
Server-side scripts infoStored proceduresuser defined functionsusing Google App EnginenoView functions (Map-Reduce) in JavaScript
TriggersyesCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyes infousing Google Cloud DataflowConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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 containersEventual Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID at container levelno infoatomic operations within a document possible
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoOptimistic locking
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.yesnoyesno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess 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 for users can be defined per database
More information provided by the system vendor
EXASOLGoogle Cloud DatastoreGridDBIBM Cloudant
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
EXASOLGoogle Cloud DatastoreGridDBIBM Cloudant
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