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DBMS > Badger vs. Citus vs. Google Cloud Bigtable vs. InterSystems Caché

System Properties Comparison Badger vs. Citus vs. Google Cloud Bigtable vs. InterSystems Caché

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonCitus  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInterSystems Caché  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A multi-model DBMS and application server
Primary database modelKey-value storeRelational DBMSKey-value store
Wide column store
Key-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websitegithub.com/­dgraph-io/­badgerwww.citusdata.comcloud.google.com/­bigtablewww.intersystems.com/­products/­cache
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.citusdata.comcloud.google.com/­bigtable/­docsdocs.intersystems.com
DeveloperDGraph LabsGoogleInterSystems
Initial release2017201020151997
Current release8.1, December 20182018.1.4, May 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL, commercial license also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxhostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freedepending on used data model
Typing infopredefined data types such as float or datenoyesnoyes
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.noyes infospecific XML type available, but no XML query functionalitynoyes
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsnoyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGo.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication infoother methods possible by using 3rd party extensionsInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsACID
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.nononoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles

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More resources
BadgerCitusGoogle Cloud BigtableInterSystems Caché
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