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DBMS > Apache Druid vs. Hive vs. PouchDB vs. Prometheus vs. Spark SQL

System Properties Comparison Apache Druid vs. Hive vs. PouchDB vs. Prometheus vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHive  Xexclude from comparisonPouchDB  Xexclude from comparisonPrometheus  Xexclude from comparisonSpark SQL  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 HadoopJavaScript DBMS with an API inspired by CouchDBOpen-source Time Series DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument storeTime 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
Score2.28
Rank#115  Overall
#21  Document stores
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitedruid.apache.orghive.apache.orgpouchdb.comprometheus.iospark.apache.org/­sql
Technical documentationdruid.apache.org/­docs/­latest/­designcwiki.apache.org/­confluence/­display/­Hive/­Homepouchdb.com/­guidesprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsApache Software Foundation infoinitially developed by FacebookApache Software FoundationApache Software Foundation
Initial release20122012201220152014
Current release29.0.1, April 20243.1.3, April 20227.1.1, June 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaScriptGoScala
Server operating systemsLinux
OS X
Unix
All OS with a Java VMserver-less, requires a JavaScript environment (browser, Node.js)Linux
Windows
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoNumeric data onlyyes
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 infoImport of XML data possibleno
Secondary indexesyesyesyes infovia viewsnono
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsnonoSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
HTTP REST infoonly for PouchDB Server
JavaScript API
RESTful HTTP/JSON APIJDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
PHP
Python
JavaScript.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceView functions in JavaScriptnono
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infowith a proxy-based framework, named couchdb-loungeShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistencynone
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
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 rolesnonono

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Apache DruidHivePouchDBPrometheusSpark SQL
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