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DBMS > Apache Druid vs. Apache Impala vs. Apache IoTDB vs. Quasardb vs. Trafodion

System Properties Comparison Apache Druid vs. Apache Impala vs. Apache IoTDB vs. Quasardb vs. Trafodion

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonQuasardb  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for HadoopAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkDistributed, high-performance timeseries databaseTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websitedruid.apache.orgimpala.apache.orgiotdb.apache.orgquasar.aitrafodion.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldoc.quasar.ai/­mastertrafodion.apache.org/­documentation.html
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationquasardbApache Software Foundation, originally developed by HP
Initial release20122013201820092014
Current release29.0.1, April 20244.1.0, June 20221.1.0, April 20233.14.1, January 20242.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2Open Source infoApache Version 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++JavaC++C++, Java
Server operating systemsLinux
OS X
Unix
LinuxAll OS with a Java VM (>= 1.8)BSD
Linux
OS X
Windows
Linux
Data schemeyes infoschema-less columns are supportedyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binaryyes
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.nonononono
Secondary indexesyesyesyesyes infowith tagsyes
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsSQL-like query languageSQL-like query languageyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
Native API
HTTP APIADO.NET
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesnoJava Stored Procedures
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replication with selectable replication factoryes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceIntegration with Hadoop and Sparkwith Hadoop integrationyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infoTransient modeno
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 roles infobased on Apache Sentry and KerberosyesCryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard

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More resources
Apache DruidApache ImpalaApache IoTDBQuasardbTrafodion
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