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DBMS > Apache Druid vs. eXtremeDB vs. Heroic vs. Microsoft Azure Data Explorer vs. Titan

System Properties Comparison Apache Druid vs. eXtremeDB vs. Heroic vs. Microsoft Azure Data Explorer vs. Titan

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisoneXtremeDB  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataNatively in-memory DBMS with options for persistency, high-availability and clusteringTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platformTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS
Time Series DBMS
Time Series DBMSRelational DBMS infocolumn orientedGraph 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
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
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitedruid.apache.orgwww.mcobject.comgithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorergithub.com/­thinkaurelius/­titan
Technical documentationdruid.apache.org/­docs/­latest/­designwww.mcobject.com/­docs/­extremedb.htmspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorergithub.com/­thinkaurelius/­titan/­wiki
DeveloperApache Software Foundation and contributorsMcObjectSpotifyMicrosoftAurelius, owned by DataStax
Initial release20122001201420192012
Current release29.0.1, April 20248.2, 2021cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache 2.0commercialOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++JavaJava
Server operating systemsLinux
OS X
Unix
AIX
HP-UX
Linux
macOS
Solaris
Windows
hostedLinux
OS X
Unix
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeFixed 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.nono infosupport of XML interfaces availablenoyes
Secondary indexesyesyesyes infovia Elasticsearchall fields are automatically indexedyes
SQL infoSupport of SQLSQL for queryingyes infowith the option: eXtremeSQLnoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Clojure
Java
Python
Server-side scripts infoStored proceduresnoyesnoYes, possible languages: KQL, Python, Ryes
Triggersnoyes infoby defining eventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning / shardingShardingSharding infoImplicit feature of the cloud serviceyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yesyes 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-sparkyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnonoyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAzure Active Directory AuthenticationUser authentification and security via Rexster Graph Server
More information provided by the system vendor
Apache DruideXtremeDBHeroicMicrosoft Azure Data ExplorerTitan
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,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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Apache DruideXtremeDBHeroicMicrosoft Azure Data ExplorerTitan
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