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DBMS > Drizzle vs. Heroic vs. Microsoft Azure Data Explorer vs. Neo4j vs. Stardog

System Properties Comparison Drizzle vs. Heroic vs. Microsoft Azure Data Explorer vs. Neo4j vs. Stardog

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNeo4j  Xexclude from comparisonStardog  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platformScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infocolumn orientedGraph 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score44.47
Rank#23  Overall
#1  Graph DBMS
Score2.05
Rank#129  Overall
#11  Graph DBMS
#6  RDF stores
Websitegithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorerneo4j.comwww.stardog.com
Technical documentationspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorerneo4j.com/­docsdocs.stardog.com
DeveloperDrizzle project, originally started by Brian AkerSpotifyMicrosoftNeo4j, Inc.Stardog-Union
Initial release20082014201920072010
Current release7.2.4, September 2012cloud service with continuous releases5.19, April 20247.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache 2.0commercialOpen Source infoGPL version3, commercial licenses availablecommercial 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

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 languageC++JavaJava, ScalaJava
Server operating systemsFreeBSD
Linux
OS X
hostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)schema-free and schema-optionalschema-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.noyesno infoImport/export of XML data possible
Secondary indexesyesyes infovia Elasticsearchall fields are automatically indexedyes infopluggable indexing subsystem, by default Apache Luceneyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyes infowith proprietary extensionsnoKusto Query Language (KQL), SQL subsetnoYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBCHQL (Heroic Query Language, a JSON-based language)
HTTP 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
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 languagesC
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnonoYes, possible languages: KQL, Python, Ryes infoUser defined Procedures and Functionsuser defined functions and aggregates, HTTP Server extensions in Java
Triggersno infohooks for callbacks inside the server can be used.noyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handleryes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceyes using Neo4j Fabricnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes 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 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 systemEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesnonoyes infoRelationships in graphsyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID
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.nonoyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAzure Active Directory AuthenticationUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Access rights for users and roles
More information provided by the system vendor
DrizzleHeroicMicrosoft Azure Data ExplorerNeo4jStardog
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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