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DBMS > Apache Druid vs. Ehcache vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. Stardog

System Properties Comparison Apache Druid vs. Ehcache vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. Stardog

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEhcache  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgres-XL  Xexclude from comparisonStardog  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 optionsFully managed big data interactive analytics platformBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeRelational DBMS infocolumn orientedRelational DBMSGraph DBMS
RDF store
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.85
Rank#96  Overall
#50  Relational DBMS
#6  Time Series DBMS
Score4.79
Rank#66  Overall
#8  Key-value stores
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score0.43
Rank#260  Overall
#119  Relational DBMS
Score1.93
Rank#121  Overall
#10  Graph DBMS
#6  RDF stores
Websitedruid.apache.orgwww.ehcache.orgazure.microsoft.com/­services/­data-explorerwww.postgres-xl.orgwww.stardog.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.ehcache.org/­documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgres-xl.org/­documentationdocs.stardog.com
DeveloperApache Software Foundation and contributorsTerracotta Inc, owned by Software AGMicrosoftStardog-Union
Initial release2012200920192014 infosince 2012, originally named StormDB2010
Current release30.0.0, June 20243.10.0, March 2022cloud service with continuous releases10 R1, October 20187.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoMozilla public licensecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaCJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VMhostedLinux
macOS
Linux
macOS
Windows
Data schemeyes infoschema-less columns are supportedschema-freeFixed schema with schema-less datatypes (dynamic)yesschema-free and OWL/RDFS-schema support
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-typesyesyes
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.nonoyesyes infoXML type, but no XML query functionalityno infoImport/export of XML data possible
Secondary indexesyesnoall fields are automatically indexedyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLSQL for queryingnoKusto Query Language (KQL), SQL subsetyes infodistributed, parallel query executionYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JCacheMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Java.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Ruser defined functionsuser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes infoCache Event Listenersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoby using Terracotta ServerSharding infoImplicit feature of the cloud servicehorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoby using Terracotta Serveryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynononoyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infosupports JTA and can work as an XA resourcenoACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAzure Active Directory Authenticationfine grained access rights according to SQL-standardAccess rights for users and roles

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More resources
Apache DruidEhcacheMicrosoft Azure Data ExplorerPostgres-XLStardog
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