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DBMS > Apache Druid vs. Datomic vs. Hive vs. Yaacomo

System Properties Comparison Apache Druid vs. Datomic vs. Hive vs. Yaacomo

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatomic  Xexclude from comparisonHive  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDatomic 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 HadoopOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Websitedruid.apache.orgwww.datomic.comhive.apache.orgyaacomo.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.datomic.comcwiki.apache.org/­confluence/­display/­Hive/­Home
DeveloperApache Software Foundation and contributorsCognitectApache Software Foundation infoinitially developed by FacebookQ2WEB GmbH
Initial release2012201220122009
Current release29.0.1, April 20241.0.6735, June 20233.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infolimited edition freeOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VMAll OS with a Java VMAndroid
Linux
Windows
Data schemeyes infoschema-less columns are supportedyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingnoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIJDBC
ODBC
Thrift
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Clojure
Java
C++
Java
PHP
Python
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsyes infouser defined functions and integration of map-reduce
TriggersnoBy using transaction functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednone infoBut extensive use of caching in the application peersShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnone infoBut extensive use of caching in the application peersselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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.noyes inforecommended only for testing and developmentyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAccess rights for users, groups and rolesfine grained access rights according to SQL-standard

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Apache DruidDatomicHiveYaacomo
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