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DBMS > Apache Druid vs. Apache Impala vs. Microsoft Azure Data Explorer vs. Quasardb vs. Trafodion

System Properties Comparison Apache Druid vs. Apache Impala vs. Microsoft Azure Data Explorer vs. Quasardb vs. Trafodion

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonMicrosoft Azure Data Explorer  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 HadoopFully managed big data interactive analytics platformDistributed, high-performance timeseries databaseTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMS infocolumn orientedTime Series DBMSRelational DBMS
Secondary database modelsDocument storeDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
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
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websitedruid.apache.orgimpala.apache.orgazure.microsoft.com/­services/­data-explorerquasar.aitrafodion.apache.org
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmldocs.microsoft.com/­en-us/­azure/­data-explorerdoc.quasar.ai/­mastertrafodion.apache.org/­documentation.html
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftquasardbApache Software Foundation, originally developed by HP
Initial release20122013201920092014
Current release29.0.1, April 20244.1.0, June 2022cloud service with continuous releases3.14.1, January 20242.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2commercialcommercial 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 servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++C++, Java
Server operating systemsLinux
OS X
Unix
LinuxhostedBSD
Linux
OS X
Windows
Linux
Data schemeyes infoschema-less columns are supportedyesFixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes 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.nonoyesnono
Secondary indexesyesyesall fields are automatically indexedyes infowith tagsyes
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetSQL-like query languageyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP APIADO.NET
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.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-reduceYes, possible languages: KQL, Python, RnoJava Stored Procedures
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud serviceSharding infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with selectable replication factoryes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparkwith Hadoop integrationyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
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.nononoyes 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 KerberosAzure Active Directory AuthenticationCryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard

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More resources
Apache DruidApache ImpalaMicrosoft Azure Data ExplorerQuasardbTrafodion
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