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DBMS > Badger vs. Google Cloud Datastore vs. GridDB vs. UniData,UniVerse

System Properties Comparison Badger vs. Google Cloud Datastore vs. GridDB vs. UniData,UniVerse

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonGridDB  Xexclude from comparisonUniData,UniVerse  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformScalable in-memory time series database optimized for IoT and Big DataMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelKey-value storeDocument storeTime Series DBMSMultivalue DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­datastoregriddb.netwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­datastore/­docsdocs.griddb.netdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperDGraph LabsGoogleToshiba CorporationRocket Software
Initial release2017200820131985
Current release5.1, August 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen 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 servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++C
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinuxAIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyes, details hereyes infonumerical, string, blob, geometry, boolean, timestampoptional
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.nonono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesGo.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresnousing Google App Enginenoyes
TriggersnoCallbacks using the Google Apps Engineyesyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflowConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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 containers
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID at container levelACID infoconfigurable
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.nonoyes
User concepts infoAccess controlnoAccess 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 according to SQL-standard and operating system based
More information provided by the system vendor
BadgerGoogle Cloud DatastoreGridDBUniData,UniVerse
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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BadgerGoogle Cloud DatastoreGridDBUniData,UniVerse
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