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DBMS > Microsoft Azure Table Storage vs. Sequoiadb vs. Spark SQL vs. TigerGraph

System Properties Comparison Microsoft Azure Table Storage vs. Sequoiadb vs. Spark SQL vs. TigerGraph

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelWide column storeDocument store
Relational DBMS
Relational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.04
Rank#77  Overall
#6  Wide column stores
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websiteazure.microsoft.com/­en-us/­services/­storage/­tableswww.sequoiadb.comspark.apache.org/­sqlwww.tigergraph.com
Technical documentationwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperMicrosoftSequoiadb Ltd.Apache Software Foundation
Initial release2012201320142017
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++
Server operating systemshostedLinuxLinux
OS X
Windows
Linux
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infooid, date, timestamp, binary, regexyesyes
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 indexesnoyesno
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsRESTful HTTP APIproprietary protocol using JSONJDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C++
Java
PHP
Python
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnoJavaScriptnoyes
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingDocument is locked during a transactionnoACID
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.nononono
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturessimple password-based access controlnoRole-based access control

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More resources
Microsoft Azure Table StorageSequoiadbSpark SQLTigerGraph
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