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DBMS > Apache Druid vs. Hive vs. SiteWhere vs. Splice Machine

System Properties Comparison Apache Druid vs. Hive vs. SiteWhere vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHive  Xexclude from comparisonSiteWhere  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality datadata warehouse software for querying and managing large distributed datasets, built on HadoopM2M integration platform for persisting/querying time series dataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series 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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.06
Rank#356  Overall
#35  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitedruid.apache.orghive.apache.orggithub.com/­sitewhere/­sitewheresplicemachine.com
Technical documentationdruid.apache.org/­docs/­latest/­designcwiki.apache.org/­confluence/­display/­Hive/­Homesitewhere1.sitewhere.io/­index.htmlsplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsApache Software Foundation infoinitially developed by FacebookSiteWhereSplice Machine
Initial release2012201220102014
Current release29.0.1, April 20243.1.3, April 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2Open Source infoCommon Public Attribution License Version 1.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VMLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyespredefined schemeyes
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.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
HTTP RESTJDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyes infoJava
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infobased on HBaseShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorselectable replication factor infobased on HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and rolesUsers with fine-grained authorization conceptAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache DruidHiveSiteWhereSplice Machine
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