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DBMS > DolphinDB vs. Faircom EDGE vs. Lovefield vs. Microsoft Azure Data Explorer vs. Tkrzw

System Properties Comparison DolphinDB vs. Faircom EDGE vs. Lovefield vs. Microsoft Azure Data Explorer vs. Tkrzw

Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonLovefield  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsEmbeddable relational database for web apps written in pure JavaScriptFully managed big data interactive analytics platformA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS infocolumn orientedKey-value store
Secondary database modelsRelational 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
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.dolphindb.comwww.faircom.com/­products/­faircom-edgegoogle.github.io/­lovefieldazure.microsoft.com/­services/­data-explorerdbmx.net/­tkrzw
Technical documentationdocs.dolphindb.cn/­en/­help200/­index.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperDolphinDB, IncFairCom CorporationGoogleMicrosoftMikio Hirabayashi
Initial release20181979201420192020
Current releasev2.00.4, January 2022V3, October 20202.1.12, February 2017cloud service with continuous releases0.9.3, August 2020
License infoCommercial or Open Sourcecommercial infofree community version availablecommercial infoRestricted, free version availableOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ANSI C, C++JavaScriptC++
Server operating systemsLinux
Windows
Android
Linux infoARM, x86
Raspbian
Windows
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedLinux
macOS
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.noyesnoyesno
Secondary indexesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLSQL-like query languageyes infoANSI SQL queriesSQL-like query language infovia JavaScript builder patternKusto 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
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
JavaScript.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesyes info.Net, JavaScript, C/C++noYes, possible languages: KQL, Python, Rno
TriggersnoyesUsing read-only observersyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningFile partitioning infoCustomizable business rules for partitioningnoneSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoSynchronous and asynchronous realtime replication based on transaction logsnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Tunable Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infowhen using SQLyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infousing MemoryDBnoyes infousing specific database classes
User concepts infoAccess controlAdministrators, Users, GroupsFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.noAzure Active Directory Authenticationno

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More resources
DolphinDBFaircom EDGE infoformerly c-treeEDGELovefieldMicrosoft Azure Data ExplorerTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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