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DBMS > Badger vs. Google Cloud Datastore vs. Microsoft Azure SQL Database vs. RavenDB vs. UniData,UniVerse

System Properties Comparison Badger vs. Google Cloud Datastore vs. Microsoft Azure SQL Database vs. RavenDB vs. UniData,UniVerse

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonRavenDB  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 PlatformDatabase as a Service offering with high compatibility to Microsoft SQL ServerOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelKey-value storeDocument storeRelational DBMSDocument storeMultivalue DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Graph DBMS
Spatial DBMS
Time Series 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
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­datastoreazure.microsoft.com/­en-us/­products/­azure-sql/­databaseravendb.netwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqlravendb.net/­docsdocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperDGraph LabsGoogleMicrosoftHibernating RhinosRocket Software
Initial release20172008201020101985
Current releaseV125.4, July 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoAGPL version 3, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++C#C
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedhostedLinux
macOS
Raspberry Pi
Windows
AIX
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datenoyes, details hereyesnooptional
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.nonoyes
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language (GQL)yesSQL-like query language (RQL)yes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP 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
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresnousing Google App EngineTransact SQLyesyes
TriggersnoCallbacks using the Google Apps Engineyesyesyes 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 Paxosyes, with always 3 replicas availableMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownoyesno
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 ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID, Cluster-wide transaction availableACID infoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAuthorization levels configured per client per databaseAccess rights according to SQL-standard and operating system based

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More resources
BadgerGoogle Cloud DatastoreMicrosoft Azure SQL Database infoformerly SQL AzureRavenDBUniData,UniVerse
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