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DBMS > Citus vs. EsgynDB vs. Google Cloud Datastore vs. Riak KV

System Properties Comparison Citus vs. EsgynDB vs. Google Cloud Datastore vs. Riak KV

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed, fault tolerant key-value store
Primary database modelRelational DBMSRelational DBMSDocument storeKey-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#123  Overall
#60  Relational DBMS
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score4.49
Rank#79  Overall
#12  Document stores
Score4.44
Rank#80  Overall
#9  Key-value stores
Websitewww.citusdata.comwww.esgyn.cncloud.google.com/­datastore
Technical documentationdocs.citusdata.comcloud.google.com/­datastore/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperEsgynGoogleOpenSource, formerly Basho Technologies
Initial release2010201520082009
Current release8.1, December 20183.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialOpen Source infoApache version 2, commercial enterprise edition
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 languageCC++, JavaErlang
Server operating systemsLinuxLinuxhostedLinux
OS X
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereno
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 indexesyesyesyesrestricted
SQL infoSupport of SQLyes infostandard, with numerous extensionsyesSQL-like query language (GQL)no
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Native Erlang Interface
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Java Stored Proceduresusing Google App EngineErlang
TriggersyesnoCallbacks using the Google Apps Engineyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication between multi datacentersMulti-source replication using Paxosselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.Eventual Consistency
Foreign keys infoReferential integrityyesyesyes infovia ReferenceProperties or Ancestor pathsno infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes, using Riak Security

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More resources
CitusEsgynDBGoogle Cloud DatastoreRiak KV
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