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DBMS > Microsoft Azure Synapse Analytics vs. openGemini vs. Spark SQL vs. SQream DB

System Properties Comparison Microsoft Azure Synapse Analytics vs. openGemini vs. Spark SQL vs. SQream DB

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Editorial information provided by DB-Engines
NameMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonopenGemini  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerAn 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 processinga GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.01
Rank#375  Overall
#39  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websiteazure.microsoft.com/­services/­synapse-analyticswww.opengemini.org
github.com/­openGemini
spark.apache.org/­sqlsqream.com
Technical documentationdocs.microsoft.com/­azure/­synapse-analyticsdocs.opengemini.org/­guidespark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperMicrosoftHuawei and openGemini communityApache Software FoundationSQream Technologies
Initial release2016202220142017
Current release1.1, July 20233.5.0 ( 2.13), September 20232022.1.6, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open 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++GoScalaC++, CUDA, Haskell, Java, Scala
Server operating systemshostedLinux
Windows
Linux
OS X
Windows
Linux
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesInteger, Float, Boolean, Stringyesyes, ANSI Standard SQL 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.nonono
Secondary indexesyesyesnono
SQL infoSupport of SQLyesSQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
HTTP RESTJDBC
ODBC
.Net
JDBC
ODBC
Supported programming languagesC#
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresTransact SQLnonouser defined functions in Python
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingyes, utilizing Spark Corehorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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.yesno
User concepts infoAccess controlyesAdministrators and common users accountsno

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More resources
Microsoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseopenGeminiSpark SQLSQream DB
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