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DBMS > Apache Impala vs. Apache IoTDB vs. Apache Phoenix vs. Drizzle

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Apache Phoenix vs. Drizzle

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonApache Phoenix  Xexclude from comparisonDrizzle  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.
DescriptionAnalytic 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 FlinkA scale-out RDBMS with evolutionary schema built on Apache HBaseMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Websiteimpala.apache.orgiotdb.apache.orgphoenix.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlphoenix.apache.org
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationApache Software FoundationDrizzle project, originally started by Brian Aker
Initial release2013201820142008
Current release4.1.0, June 20221.1.0, April 20235.0-HBase2, July 2018 and 4.15-HBase1, December 20197.2.4, September 2012
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoGNU GPL
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaC++
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)Linux
Unix
Windows
FreeBSD
Linux
OS X
Data schemeyesyesyes infolate-bound, schema-on-read capabilitiesyes
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-like DML and DDL statementsSQL-like query languageyesyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
JDBC
Native API
JDBCJDBC
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Java
PHP
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesuser defined functionsno
Triggersnoyesnono infohooks for callbacks inside the server can be used.
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and SparkHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyPluggable authentication mechanisms infoe.g. LDAP, HTTP

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Apache ImpalaApache IoTDBApache PhoenixDrizzle
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