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DBMS > Datomic vs. Hive vs. IBM Db2 Event Store vs. Riak KV

System Properties Comparison Datomic vs. Hive vs. IBM Db2 Event Store vs. Riak KV

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHive  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitydata warehouse software for querying and managing large distributed datasets, built on HadoopDistributed Event Store optimized for Internet of Things use casesDistributed, fault tolerant key-value store
Primary database modelRelational DBMSRelational DBMSEvent Store
Time Series DBMS
Key-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitewww.datomic.comhive.apache.orgwww.ibm.com/­products/­db2-event-store
Technical documentationdocs.datomic.comcwiki.apache.org/­confluence/­display/­Hive/­Homewww.ibm.com/­docs/­en/­db2-event-storewww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperCognitectApache Software Foundation infoinitially developed by FacebookIBMOpenSource, formerly Basho Technologies
Initial release2012201220172009
Current release1.0.6735, June 20233.1.3, April 20222.03.2.0, December 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2commercial infofree developer edition availableOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaC and C++Erlang
Server operating systemsAll OS with a Java VMAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nonono
Secondary indexesyesyesnorestricted
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infothrough the embedded Spark runtimeno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Thrift
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
Supported programming languagesClojure
Java
C++
Java
PHP
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
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 proceduresyes infoTransaction Functionsyes infouser defined functions and integration of map-reduceyesErlang
TriggersBy using transaction functionsnonoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersselectable replication factorActive-active shard replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
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 developmentyes
User concepts infoAccess controlnoAccess rights for users, groups and rolesfine grained access rights according to SQL-standardyes, using Riak Security

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DatomicHiveIBM Db2 Event StoreRiak KV
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