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DBMS > Apache Druid vs. Derby vs. eXtremeDB vs. Microsoft Azure Data Explorer vs. SAP HANA

System Properties Comparison Apache Druid vs. Derby vs. eXtremeDB vs. Microsoft Azure Data Explorer vs. SAP HANA

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDB  Xexclude from comparisoneXtremeDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSAP HANA  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Natively in-memory DBMS with options for persistency, high-availability and clusteringFully managed big data interactive analytics platformIn-memory, column based data store. Available as appliance or cloud service
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument 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
Document store
Graph DBMS infowith SAP Hana, Enterprise Edition
Spatial DBMS
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
Score4.60
Rank#70  Overall
#38  Relational DBMS
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score44.27
Rank#23  Overall
#16  Relational DBMS
Websitedruid.apache.orgdb.apache.org/­derbywww.mcobject.comazure.microsoft.com/­services/­data-explorerwww.sap.com/­products/­hana.html
Technical documentationdruid.apache.org/­docs/­latest/­designdb.apache.org/­derby/­manuals/­index.htmlwww.mcobject.com/­docs/­extremedb.htmdocs.microsoft.com/­en-us/­azure/­data-explorerhelp.sap.com/­hana
DeveloperApache Software Foundation and contributorsApache Software FoundationMcObjectMicrosoftSAP
Initial release20121997200120192010
Current release29.0.1, April 202410.17.1.0, November 20238.2, 2021cloud service with continuous releases2.0 SPS07 (April 4, 2023), April 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache version 2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno infoalso available as a cloud based service
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC and C++
Server operating systemsLinux
OS X
Unix
All OS with a Java VMAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedAppliance or cloud-service
Data schemeyes infoschema-less columns are supportedyesyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.noyesno infosupport of XML interfaces availableyesno
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL for queryingyesyes infowith the option: eXtremeSQLKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Java.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoJava Stored ProceduresyesYes, possible languages: KQL, Python, RSQLScript, R
Triggersnoyesyes infoby defining eventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednonehorizontal partitioning / shardingSharding infoImplicit feature of the cloud serviceyes
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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.noyesyesnoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardAzure Active Directory Authenticationyes
More information provided by the system vendor
Apache DruidDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDBeXtremeDBMicrosoft Azure Data ExplorerSAP HANA
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
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Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
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Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
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Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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Apache DruidDerby infooften called Apache Derby, originally IBM Cloudscape; contained in the Java SDK as JavaDBeXtremeDBMicrosoft Azure Data ExplorerSAP HANA
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