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DBMS > Datomic vs. IBM Cloudant vs. Riak KV vs. Spark SQL

System Properties Comparison Datomic vs. IBM Cloudant vs. Riak KV vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonRiak KV  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityDatabase as a Service offering based on Apache CouchDBDistributed, fault tolerant key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score2.75
Rank#104  Overall
#19  Document stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.datomic.comwww.ibm.com/­products/­cloudantspark.apache.org/­sql
Technical documentationdocs.datomic.comcloud.ibm.com/­docs/­Cloudantwww.tiot.jp/­riak-docs/­riak/­kv/­latestspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014OpenSource, formerly Basho TechnologiesApache Software Foundation
Initial release2012201020092014
Current release1.0.6735, June 20233.2.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0
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 languageJava, ClojureErlangErlangScala
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnonoyes
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 indexesyesyesrestrictedno
SQL infoSupport of SQLnononoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIRESTful HTTP/JSON APIHTTP API
Native Erlang Interface
JDBC
ODBC
Supported programming languagesClojure
Java
C#
Java
JavaScript
Objective-C
PHP
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
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction FunctionsView functions (Map-Reduce) in JavaScriptErlangno
TriggersBy using transaction functionsyesyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infono "single point of failure"yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoatomic operations within a document possiblenono
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic lockingyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnono
User concepts infoAccess controlnoAccess rights for users can be defined per databaseyes, using Riak Securityno

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DatomicIBM CloudantRiak KVSpark SQL
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