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DBMS > Badger vs. Google Cloud Bigtable vs. Kinetica vs. RethinkDB

System Properties Comparison Badger vs. Google Cloud Bigtable vs. Kinetica vs. RethinkDB

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKinetica  Xexclude from comparisonRethinkDB  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully vectorized database across both GPUs and CPUsDBMS for the Web with a mechanism to push updated query results to applications in realtime.
Primary database modelKey-value storeKey-value store
Wide column store
Relational DBMSDocument store
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score2.74
Rank#105  Overall
#19  Document stores
Websitegithub.com/­dgraph-io/­badgercloud.google.com/­bigtablewww.kinetica.comrethinkdb.com
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgercloud.google.com/­bigtable/­docsdocs.kinetica.comrethinkdb.com/­docs
DeveloperDGraph LabsGoogleKineticaThe Linux Foundation infosince July 2017
Initial release2017201520122009
Current release7.1, August 20212.4.1, August 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache Version 2
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++C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenonoyesyes infostring, binary, float, bool, date, geometry
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 indexesnonoyesyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGoC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Server-side scripts infoStored proceduresnonouser defined functions
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeClient-side triggers through changefeeds
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding inforange based
Replication methods infoMethods for redundantly storing data on multiple nodesnoneInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsnoAtomic single-document operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC based
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 infoGPU vRAM or System RAMno
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelyes infousers and table-level permissions

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More resources
BadgerGoogle Cloud BigtableKineticaRethinkDB
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