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DBMS > Citus vs. Google Cloud Bigtable vs. HarperDB vs. IBM Cloudant

System Properties Comparison Citus vs. Google Cloud Bigtable vs. HarperDB vs. IBM Cloudant

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonIBM Cloudant  Xexclude from comparison
DescriptionScalable 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.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Database as a Service offering based on Apache CouchDB
Primary database modelRelational DBMSKey-value store
Wide column store
Document storeDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.60
Rank#244  Overall
#38  Document stores
Score2.75
Rank#104  Overall
#19  Document stores
Websitewww.citusdata.comcloud.google.com/­bigtablewww.harperdb.iowww.ibm.com/­products/­cloudant
Technical documentationdocs.citusdata.comcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docscloud.ibm.com/­docs/­Cloudant
DeveloperGoogleHarperDBIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014
Initial release2010201520172010
Current release8.1, December 20183.1, August 2021
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercial infofree community edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCNode.jsErlang
Server operating systemsLinuxhostedLinux
OS X
hosted
Data schemeyesschema-freedynamic schemaschema-free
Typing infopredefined data types such as float or dateyesnoyes infoJSON data typesno
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.yes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoSQL-like data manipulation statementsno
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)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C#
Java
JavaScript
Objective-C
PHP
Ruby
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noCustom Functions infosince release 3.1View functions (Map-Reduce) in JavaScript
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be definedMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsAtomic execution of specific operationsno infoatomic operations within a document possible
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoOptimistic locking
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlfine 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 and rolesAccess rights for users can be defined per database

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More resources
CitusGoogle Cloud BigtableHarperDBIBM Cloudant
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