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DBMS > Apache Druid vs. Microsoft Azure Data Explorer vs. Neo4j vs. PostgreSQL

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

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNeo4j  Xexclude from comparisonPostgreSQL  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 offeringsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS infocolumn orientedGraph DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
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
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
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
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score44.89
Rank#21  Overall
#1  Graph DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Websitedruid.apache.orgazure.microsoft.com/­services/­data-explorerneo4j.comwww.postgresql.org
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.microsoft.com/­en-us/­azure/­data-explorerneo4j.com/­docswww.postgresql.org/­docs
DeveloperApache Software Foundation and contributorsMicrosoftNeo4j, Inc.PostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2012201920071989 info1989: Postgres, 1996: PostgreSQL
Current release29.0.1, April 2024cloud service with continuous releases5.20, May 202416.3, May 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoGPL version3, commercial licenses availableOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ScalaC
Server operating systemsLinux
OS X
Unix
hostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyes infoschema-less columns are supportedFixed schema with schema-less datatypes (dynamic)schema-free and schema-optionalyes
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-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.noyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesall fields are automatically indexedyes infopluggable indexing subsystem, by default Apache Luceneyes
SQL infoSupport of SQLSQL for queryingKusto Query Language (KQL), SQL subsetnoyes infostandard with numerous extensions
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
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Ryes infoUser defined Procedures and Functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handleryes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoImplicit feature of the cloud serviceyes using Neo4j Fabricpartitioning by range, list and (since PostgreSQL 11) by hash
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 onlySource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
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
Immediate Consistency
Foreign keys infoReferential integritynonoyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
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)fine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruidMicrosoft Azure Data ExplorerNeo4jPostgreSQL
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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