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DBMS > Apache Doris vs. EsgynDB vs. Microsoft Azure SQL Database vs. SiteWhere

System Properties Comparison Apache Doris vs. EsgynDB vs. Microsoft Azure SQL Database vs. SiteWhere

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Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonEsgynDB  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSiteWhere  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionDatabase as a Service offering with high compatibility to Microsoft SQL ServerM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websitedoris.apache.org
github.com/­apache/­doris
www.esgyn.cnazure.microsoft.com/­en-us/­products/­azure-sql/­databasegithub.com/­sitewhere/­sitewhere
Technical documentationgithub.com/­apache/­doris/­wikidocs.microsoft.com/­en-us/­azure/­azure-sqlsitewhere1.sitewhere.io/­index.html
DeveloperApache Software Foundation, originally contributed from BaiduEsgynMicrosoftSiteWhere
Initial release2017201520102010
Current release1.2.2, February 2023V12
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaC++Java
Server operating systemsLinuxLinuxhostedLinux
OS X
Windows
Data schemeyesyesyespredefined scheme
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesyesyesno
APIs and other access methodsJDBC
MySQL client
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
HTTP REST
Supported programming languagesJavaAll languages supporting JDBC/ODBC/ADO.Net.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsJava Stored ProceduresTransact SQL
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication between multi datacentersyes, with always 3 replicas availableselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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 controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardUsers with fine-grained authorization concept

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More resources
Apache DorisEsgynDBMicrosoft Azure SQL Database infoformerly SQL AzureSiteWhere
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Recent citations in the news

Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
5 June 2024, hackernoon.com

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How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

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24 June 2022, InfoWorld

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8 May 2024, hackernoon.com

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