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DBMS > DolphinDB vs. Graph Engine vs. H2 vs. Microsoft Azure Data Explorer vs. Neo4j

System Properties Comparison DolphinDB vs. Graph Engine vs. H2 vs. Microsoft Azure Data Explorer vs. Neo4j

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonH2  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNeo4j  Xexclude from comparison
DescriptionDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Fully managed big data interactive analytics platformScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings
Primary database modelTime Series DBMSGraph DBMS
Key-value store
Relational DBMSRelational DBMS infocolumn orientedGraph DBMS
Secondary database modelsRelational DBMSSpatial DBMSDocument 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
Score4.13
Rank#80  Overall
#6  Time Series DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score44.46
Rank#23  Overall
#1  Graph DBMS
Websitewww.dolphindb.comwww.graphengine.iowww.h2database.comazure.microsoft.com/­services/­data-explorerneo4j.com
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlwww.graphengine.io/­docs/­manualwww.h2database.com/­html/­main.htmldocs.microsoft.com/­en-us/­azure/­data-explorerneo4j.com/­docs
DeveloperDolphinDB, IncMicrosoftThomas MuellerMicrosoftNeo4j, Inc.
Initial release20182010200520192007
Current releasev2.00.4, January 20222.2.220, July 2023cloud service with continuous releases5.19, April 2024
License infoCommercial or Open Sourcecommercial infofree community version availableOpen Source infoMIT LicenseOpen Source infodual-licence (Mozilla public license, Eclipse public license)commercialOpen Source infoGPL version3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononoyesno
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++.NET and CJavaJava, Scala
Server operating systemsLinux
Windows
.NETAll OS with a Java VMhostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Data schemeyesyesyesFixed schema with schema-less datatypes (dynamic)schema-free and schema-optional
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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.nononoyes
Secondary indexesyesyesall fields are automatically indexedyes infopluggable indexing subsystem, by default Apache Lucene
SQL infoSupport of SQLSQL-like query languagenoyesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
RESTful HTTP APIJDBC
ODBC
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
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C#
C++
F#
Visual Basic
Java.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyesyesJava Stored Procedures and User-Defined FunctionsYes, possible languages: KQL, Python, Ryes infoUser defined Procedures and Functions
Triggersnonoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infovia event handler
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioningnoneSharding infoImplicit feature of the cloud serviceyes using Neo4j Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesyesWith clustering: 2 database servers on different computers operate on identical copies of a databaseyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Causal Clustering using Raft protocol infoavailable in in Enterprise Version only
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integritynonoyesnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlAdministrators, Users, Groupsfine grained access rights according to SQL-standardAzure Active Directory AuthenticationUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
DolphinDBGraph Engine infoformer name: TrinityH2Microsoft Azure Data ExplorerNeo4j
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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