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DBMS > Apache Druid vs. Geode vs. Microsoft Azure Data Explorer vs. RethinkDB vs. STSdb

System Properties Comparison Apache Druid vs. Geode vs. Microsoft Azure Data Explorer vs. RethinkDB vs. STSdb

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGeode  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRethinkDB  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesFully managed big data interactive analytics platformDBMS for the Web with a mechanism to push updated query results to applications in realtime.Key-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeRelational DBMS infocolumn orientedDocument storeKey-value 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
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
Score1.86
Rank#134  Overall
#24  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.66
Rank#107  Overall
#20  Document stores
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitedruid.apache.orggeode.apache.orgazure.microsoft.com/­services/­data-explorerrethinkdb.comgithub.com/­STSSoft/­STSdb4
Technical documentationdruid.apache.org/­docs/­latest/­designgeode.apache.org/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerrethinkdb.com/­docs
DeveloperApache Software Foundation and contributorsOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.MicrosoftThe Linux Foundation infosince July 2017STS Soft SC
Initial release20122002201920092011
Current release29.0.1, April 20241.1, February 2017cloud service with continuous releases2.4.1, August 20204.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2; commercial licenses available as GemfirecommercialOpen Source infoApache Version 2Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++C#
Server operating systemsLinux
OS X
Unix
All OS with a Java VM infothe JDK (8 or later) is also requiredhostedLinux
OS X
Windows
Windows
Data schemeyes infoschema-less columns are supportedschema-freeFixed 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 infostring, binary, float, bool, date, geometryyes infoprimitive types and user defined types (classes)
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.nonoyesno
Secondary indexesyesnoall fields are automatically indexedyesno
SQL infoSupport of SQLSQL for queryingSQL-like query language (OQL)Kusto Query Language (KQL), SQL subsetnono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Java Client API
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
C#
Java
Server-side scripts infoStored proceduresnouser defined functionsYes, possible languages: KQL, Python, Rno
Triggersnoyes infoCache Event Listenersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyClient-side triggers through changefeedsno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingSharding infoImplicit feature of the cloud serviceSharding inforange basednone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes, on a single nodenoAtomic single-document operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC basedyes
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.noyesnono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights per client and object definableAzure Active Directory Authenticationyes infousers and table-level permissionsno

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More resources
Apache DruidGeodeMicrosoft Azure Data ExplorerRethinkDBSTSdb
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