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DBMS > Apache Druid vs. Ehcache vs. Heroic vs. Microsoft Azure Data Explorer

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

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEhcache  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA widely adopted Java cache with tiered storage optionsTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platform
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeTime Series DBMSRelational DBMS infocolumn oriented
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
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score5.23
Rank#68  Overall
#8  Key-value stores
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitedruid.apache.orgwww.ehcache.orggithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorer
Technical documentationdruid.apache.org/­docs/­latest/­designwww.ehcache.org/­documentationspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperApache Software Foundation and contributorsTerracotta Inc, owned by Software AGSpotifyMicrosoft
Initial release2012200920142019
Current release29.0.1, April 20243.10.0, March 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VMhosted
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)
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-types
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.nononoyes
Secondary indexesyesnoyes infovia Elasticsearchall fields are automatically indexed
SQL infoSupport of SQLSQL for queryingnonoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JCacheHQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Java.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnononoYes, possible languages: KQL, Python, R
Triggersnoyes infoCache Event Listenersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoby using Terracotta ServerShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoby using Terracotta Serveryesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infosupports JTA and can work as an XA resourcenono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes
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 systemnoAzure Active Directory Authentication

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More resources
Apache DruidEhcacheHeroicMicrosoft Azure Data Explorer
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