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DBMS > Apache Druid vs. Microsoft Azure Data Explorer vs. Neo4j vs. OrientDB vs. OushuDB

System Properties Comparison Apache Druid vs. Microsoft Azure Data Explorer vs. Neo4j vs. OrientDB vs. OushuDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNeo4j  Xexclude from comparisonOrientDB  Xexclude from comparisonOushuDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataFully managed big data interactive analytics platformScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsMulti-model DBMS (Document, Graph, Key/Value)A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedGraph DBMSDocument store
Graph DBMS
Key-value store
Relational 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
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score44.46
Rank#23  Overall
#1  Graph DBMS
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Score0.04
Rank#363  Overall
#154  Relational DBMS
Websitedruid.apache.orgazure.microsoft.com/­services/­data-explorerneo4j.comorientdb.orgwww.oushu.com/­product/­oushuDB
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.microsoft.com/­en-us/­azure/­data-explorerneo4j.com/­docswww.orientdb.com/­docs/­last/­index.htmlwww.oushu.com/­documentation
DeveloperApache Software Foundation and contributorsMicrosoftNeo4j, Inc.OrientDB LTD; CallidusCloud; SAPOushu
Initial release2012201920072010
Current release29.0.1, April 2024cloud service with continuous releases5.19, April 20243.2.29, March 20244.0.1, August 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoGPL version3, commercial licenses availableOpen Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageJavaJava, ScalaJava
Server operating systemsLinux
OS X
Unix
hostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
All OS with a Java JDK (>= JDK 6)Linux
Data schemeyes infoschema-less columns are supportedFixed schema with schema-less datatypes (dynamic)schema-free and schema-optionalschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")yes
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesyes
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
Secondary indexesyesall fields are automatically indexedyes infopluggable indexing subsystem, by default Apache Luceneyesyes
SQL infoSupport of SQLSQL for queryingKusto Query Language (KQL), SQL subsetnoSQL-like query language, no joinsFull-featured ANSI SQL support
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C
C++
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Ryes infoUser defined Procedures and FunctionsJava, Javascriptyes
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handlerHooksyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoImplicit feature of the cloud serviceyes using Neo4j FabricShardingyes
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Causal Clustering using Raft protocol infoavailable in in Enterprise Version onlyMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono infocould be achieved with distributed queriesHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integritynonoyes infoRelationships in graphsyes inforelationship in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nono
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAzure Active Directory AuthenticationUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Access rights for users and roles; record level security configurableKerberos, SSL and role based access
More information provided by the system vendor
Apache DruidMicrosoft Azure Data ExplorerNeo4jOrientDBOushuDB
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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