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DBMS > DolphinDB vs. Firebase Realtime Database vs. Graph Engine vs. H2 vs. Microsoft Azure Data Explorer

System Properties Comparison DolphinDB vs. Firebase Realtime Database vs. Graph Engine vs. H2 vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonH2  Xexclude from comparisonMicrosoft Azure Data Explorer  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.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.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 platform
Primary database modelTime Series DBMSDocument storeGraph DBMS
Key-value store
Relational DBMSRelational DBMS infocolumn oriented
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
Score4.23
Rank#82  Overall
#6  Time Series DBMS
Score15.00
Rank#39  Overall
#6  Document stores
Score0.62
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score8.22
Rank#50  Overall
#32  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Websitewww.dolphindb.comfirebase.google.com/­products/­realtime-databasewww.graphengine.iowww.h2database.comazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmlfirebase.google.com/­docs/­databasewww.graphengine.io/­docs/­manualwww.h2database.com/­html/­main.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDolphinDB, IncGoogle infoacquired by Google 2014MicrosoftThomas MuellerMicrosoft
Initial release20182012201020052019
Current releasev2.00.4, January 20222.2.220, July 2023cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infofree community version availablecommercialOpen Source infoMIT LicenseOpen Source infodual-licence (Mozilla public license, Eclipse public license)commercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++.NET and CJava
Server operating systemsLinux
Windows
hosted.NETAll OS with a Java VMhosted
Data schemeyesschema-freeyesyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonononoyes
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languagenonoyesKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
Android
iOS
JavaScript API
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
Java
JavaScript
Objective-C
C#
C++
F#
Visual Basic
Java.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyeslimited functionality with using 'rules'yesJava Stored Procedures and User-Defined FunctionsYes, possible languages: KQL, Python, R
TriggersnoCallbacks are triggered when data changesnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioningnoneSharding infoImplicit feature of the cloud service
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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesyesnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
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, Groupsyes, based on authentication and database rulesfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
DolphinDBFirebase Realtime DatabaseGraph Engine infoformer name: TrinityH2Microsoft Azure Data Explorer
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