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DBMS > AllegroGraph vs. Databricks vs. Datomic vs. Hive vs. JSqlDb

System Properties Comparison AllegroGraph vs. Databricks vs. Datomic vs. Hive vs. JSqlDb

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonDatabricks  Xexclude from comparisonDatomic  Xexclude from comparisonHive  Xexclude from comparisonJSqlDb  Xexclude from comparison
JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Datomic 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 HadoopJavaScript Query Language Database, stores JavaScript objects and primitives
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document store
Relational DBMS
Relational DBMSRelational DBMSDocument store
Object oriented DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Websiteallegrograph.comwww.databricks.comwww.datomic.comhive.apache.orgjsqldb.org (offline)
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.databricks.comdocs.datomic.comcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperFranz Inc.DatabricksCognitectApache Software Foundation infoinitially developed by FacebookKonrad von Backstrom
Initial release20042013201220122018
Current release8.0, December 20231.0.7075, December 20233.1.3, April 20220.8, December 2018
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialcommercial infolimited edition freeOpen Source infoApache Version 2Open Source
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureJava
Server operating systemsLinux
OS X
Windows
hostedAll OS with a Java VMAll OS with a Java VMLinux
macOS
Windows
Data schemeyes infoRDF schemasFlexible Schema (defined schema, partial schema, schema free)yesyesschema-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.no infobulk load of XML files possibleyesnono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSPARQL is used as query languagewith Databricks SQLnoSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Thrift
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Python
R
Scala
Clojure
Java
C++
Java
PHP
Python
JavaScript
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functions and aggregatesyes infoTransaction Functionsyes infouser defined functions and integration of map-reducefunctions in JavaScript
TriggersyesBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodeswith Federationnone infoBut extensive use of caching in the application peersShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesnone infoBut extensive use of caching in the application peersselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infousing RocksDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes inforecommended only for testing and development
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnoAccess rights for users, groups and roles
More information provided by the system vendor
AllegroGraphDatabricksDatomicHiveJSqlDb
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Supported database models : In addition to the Document store and Relational DBMS...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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