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DBMS > Apache Druid vs. Apache Impala vs. Apache IoTDB vs. Drizzle vs. Riak TS

System Properties Comparison Apache Druid vs. Apache Impala vs. Apache IoTDB vs. Drizzle vs. Riak TS

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonDrizzle  Xexclude from comparisonRiak TS  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle 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 FlinkMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.33
Rank#99  Overall
#51  Relational DBMS
#7  Time Series DBMS
Score15.06
Rank#39  Overall
#24  Relational DBMS
Score1.19
Rank#183  Overall
#15  Time Series DBMS
Score0.28
Rank#308  Overall
#27  Time Series DBMS
Websitedruid.apache.orgimpala.apache.orgiotdb.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.tiot.jp/­riak-docs/­riak/­ts/­latest
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationDrizzle project, originally started by Brian AkerOpen Source, formerly Basho Technologies
Initial release20122013201820082015
Current release29.0.0, February 20244.1.0, June 20221.1.0, April 20237.2.4, September 20123.0.0, September 2022
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoGNU GPLOpen Source
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaC++Erlang
Server operating systemsLinux
OS X
Unix
LinuxAll OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
Linux
OS X
Data schemeyes infoschema-less columns are supportedyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononono
Secondary indexesyesyesyesyesrestricted
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsSQL-like query languageyes infowith proprietary extensionsyes, limited
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
Native API
JDBCHTTP API
Native Erlang Interface
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
C
C++
Java
PHP
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesnoErlang
Triggersnonoyesno infohooks for callbacks inside the server can be used.yes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
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 replicasMulti-source replication
Source-replica replication
selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceIntegration with Hadoop and Sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Eventual Consistency
Foreign keys infoReferential integritynononoyesno infolinks between datasets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
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 roles infobased on Apache Sentry and KerberosyesPluggable authentication mechanisms infoe.g. LDAP, HTTPno

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More resources
Apache DruidApache ImpalaApache IoTDBDrizzleRiak TS
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