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DBMS > Datomic vs. Hive vs. LeanXcale vs. Yaacomo

System Properties Comparison Datomic vs. Hive vs. LeanXcale vs. Yaacomo

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHive  Xexclude from comparisonLeanXcale  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
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 HadoopA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSKey-value store
Relational DBMS
Relational DBMS
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
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Websitewww.datomic.comhive.apache.orgwww.leanxcale.comyaacomo.com
Technical documentationdocs.datomic.comcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperCognitectApache Software Foundation infoinitially developed by FacebookLeanXcaleQ2WEB GmbH
Initial release2012201220152009
Current release1.0.6735, June 20233.1.3, April 2022
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJava
Server operating systemsAll OS with a Java VMAll OS with a Java VMAndroid
Linux
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nono
Secondary indexesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infothrough Apache Derbyyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Thrift
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
Supported programming languagesClojure
Java
C++
Java
PHP
Python
C
Java
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes infouser defined functions and integration of map-reduce
TriggersBy using transaction functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 developmentyesyes
User concepts infoAccess controlnoAccess rights for users, groups and rolesfine grained access rights according to SQL-standard

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DatomicHiveLeanXcaleYaacomo
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