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DBMS > Apache Impala vs. Apache IoTDB vs. Atos Standard Common Repository vs. Drizzle vs. Microsoft Azure AI Search

System Properties Comparison Apache Impala vs. Apache IoTDB vs. Atos Standard Common Repository vs. Drizzle vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonDrizzle  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.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 FlinkHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Search-as-a-service for web and mobile app development
Primary database modelRelational DBMSTime Series DBMSDocument store
Key-value store
Relational DBMSSearch engine
Secondary database modelsDocument storeVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Websiteimpala.apache.orgiotdb.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositoryazure.microsoft.com/­en-us/­services/­search
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmllearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationAtos Convergence CreatorsDrizzle project, originally started by Brian AkerMicrosoft
Initial release20132018201620082015
Current release4.1.0, June 20221.1.0, April 202317037.2.4, September 2012V1
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialOpen Source infoGNU GPLcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJavaC++
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)LinuxFreeBSD
Linux
OS X
hosted
Data schemeyesyesSchema and schema-less with LDAP viewsyesyes
Typing infopredefined data types such as float or dateyesyesoptionalyesyes
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.nonoyesno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languagenoyes infowith proprietary extensionsno
APIs and other access methodsJDBC
ODBC
JDBC
Native API
LDAPJDBCRESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
All languages with LDAP bindingsC
C++
Java
PHP
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnonono
Triggersnoyesyesno infohooks for callbacks inside the server can be used.no
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infocell divisionShardingSharding infoImplicit feature of the cloud service
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 replicasyesMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic execution of specific operationsACIDno
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.noyesyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosyesLDAP bind authenticationPluggable authentication mechanisms infoe.g. LDAP, HTTPyes infousing Azure authentication

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More resources
Apache ImpalaApache IoTDBAtos Standard Common RepositoryDrizzleMicrosoft Azure AI Search
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