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DBMS > Badger vs. Fauna vs. Google Cloud Datastore vs. Kingbase vs. SwayDB

System Properties Comparison Badger vs. Fauna vs. Google Cloud Datastore vs. Kingbase vs. SwayDB

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKingbase  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelKey-value storeDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Document storeRelational DBMSKey-value store
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score1.55
Rank#151  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.50
Rank#257  Overall
#119  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Websitegithub.com/­dgraph-io/­badgerfauna.comcloud.google.com/­datastorewww.kingbase.com.cnswaydb.simer.au
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.fauna.comcloud.google.com/­datastore/­docs
DeveloperDGraph LabsFauna, Inc.GoogleBeiJing KINGBASE Information technologies inc.Simer Plaha
Initial release20172014200819992018
Current releaseV8.0, August 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercialOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoScalaC and JavaScala
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedhostedLinux
Windows
Data schemeschema-freeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenonoyes, details hereyesno
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.nononoyesno
Secondary indexesnoyesyesyesno
SQL infoSupport of SQLnonoSQL-like query language (GQL)Standard with numerous extensionsno
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
Supported programming languagesGoC#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnouser defined functionsusing Google App Engineuser defined functionsno
TriggersnonoCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning infoconsistent hashingShardinghorizontal partitioning (by range, list and hash) and vertical partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationMulti-source replication using Paxosyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDAtomic execution of operations
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.nononoyes
User concepts infoAccess controlnoIdentity management, authentication, and access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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More resources
BadgerFauna infopreviously named FaunaDBGoogle Cloud DatastoreKingbaseSwayDB
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