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DBMS > Apache Druid vs. Apache Impala vs. Atos Standard Common Repository vs. Machbase Neo vs. Microsoft Azure AI Search

System Properties Comparison Apache Druid vs. Apache Impala vs. Atos Standard Common Repository vs. Machbase Neo vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparison
This system has been discontinued and will be removed 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 HadoopHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksTimeSeries DBMS for AIoT and BigDataSearch-as-a-service for web and mobile app development
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument store
Key-value store
Time Series DBMSSearch engine
Secondary database modelsDocument storeVector 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
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Websitedruid.apache.orgimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorymachbase.comazure.microsoft.com/­en-us/­services/­search
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmlmachbase.com/­dbmslearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsMachbaseMicrosoft
Initial release20122013201620132015
Current release29.0.1, April 20244.1.0, June 20221703V8.0, August 2023V1
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2commercialcommercial infofree test version availablecommercial
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 languageJavaC++JavaC
Server operating systemsLinux
OS X
Unix
LinuxLinuxLinux
macOS
Windows
hosted
Data schemeyes infoschema-less columns are supportedyesSchema 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.nonoyesnono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsnoSQL-like query languageno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
LDAPgRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBCAll languages with LDAP bindingsC
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenonono
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infocell divisionShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factoryesselectable replication factoryes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic execution of specific operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infovolatile and lookup tableno
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 KerberosLDAP bind authenticationsimple password-based access controlyes infousing Azure authentication

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More resources
Apache DruidApache ImpalaAtos Standard Common RepositoryMachbase Neo infoFormer name was InfinifluxMicrosoft Azure AI Search
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