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DBMS > Microsoft Azure Table Storage vs. openGemini vs. Spark SQL vs. Warp 10

System Properties Comparison Microsoft Azure Table Storage vs. openGemini vs. Spark SQL vs. Warp 10

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonopenGemini  Xexclude from comparisonSpark SQL  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsAn open source distributed Time Series DBMS with high concurrency, high performance, and high scalabilitySpark SQL is a component on top of 'Spark Core' for structured data processingTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelWide column storeTime Series DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.09
Rank#361  Overall
#37  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tableswww.opengemini.org
github.com/­openGemini
spark.apache.org/­sqlwww.warp10.io
Technical documentationdocs.opengemini.org/­guidespark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperMicrosoftHuawei and openGemini communityApache Software FoundationSenX
Initial release2012202220142015
Current release1.1, July 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoScalaJava
Server operating systemshostedLinux
Windows
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesInteger, Float, Boolean, Stringyesyes
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.nononono
Secondary indexesnoyesnono
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIHTTP RESTJDBC
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononoyes infoWarpScript
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingyes, utilizing Spark CoreSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesnoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingnonono
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.noyesnoyes
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesAdministrators and common users accountsnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Microsoft Azure Table StorageopenGeminiSpark SQLWarp 10
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