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DBMS > AnzoGraph DB vs. Datomic vs. Hive vs. Riak KV

System Properties Comparison AnzoGraph DB vs. Datomic vs. Hive vs. Riak KV

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonDatomic  Xexclude from comparisonHive  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationDatomic 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, fault tolerant key-value store
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSKey-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
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitecambridgesemantics.com/­anzographwww.datomic.comhive.apache.org
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdocs.datomic.comcwiki.apache.org/­confluence/­display/­Hive/­Homewww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperCambridge SemanticsCognitectApache Software Foundation infoinitially developed by FacebookOpenSource, formerly Basho Technologies
Initial release2018201220122009
Current release2.3, January 20211.0.6735, June 20233.1.3, April 20223.2.0, December 2022
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercial infolimited edition freeOpen Source infoApache Version 2Open 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, ClojureJavaErlang
Server operating systemsLinuxAll OS with a Java VMAll OS with a Java VMLinux
OS X
Data schemeSchema-free and OWL/RDFS-schema supportyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 indexesnoyesyesrestricted
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.noSQL-like DML and DDL statementsno
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
RESTful HTTP APIJDBC
ODBC
Thrift
HTTP API
Native Erlang Interface
Supported programming languagesC++
Java
Python
Clojure
Java
C++
Java
PHP
Python
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 and aggregatesyes infoTransaction Functionsyes infouser defined functions and integration of map-reduceErlang
TriggersnoBy using transaction functionsnoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingnone infoBut extensive use of caching in the application peersShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusternone infoBut extensive use of caching in the application peersselectable replication factorselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnonono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and development
User concepts infoAccess controlAccess rights for users and rolesnoAccess rights for users, groups and rolesyes, using Riak Security

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