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DBMS > Amazon Redshift vs. EJDB vs. Microsoft Azure Synapse Analytics vs. Spark SQL

System Properties Comparison Amazon Redshift vs. EJDB vs. Microsoft Azure Synapse Analytics vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonEJDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score25.94
Rank#31  Overall
#18  Relational DBMS
Score0.10
Rank#314  Overall
#41  Document stores
Score20.66
Rank#36  Overall
#22  Relational DBMS
Score22.86
Rank#35  Overall
#21  Relational DBMS
Websiteaws.amazon.com/­redshiftejdb.orgazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­redshiftgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazon (based on PostgreSQL)SoftmotionsMicrosoftApache Software Foundation
Initial release2012201220162014
Current release3.2.0, October 2021
License infoCommercial or Open SourcecommercialOpen Source infoGPLv2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCCC++Scala
Server operating systemshostedserver-lesshostedLinux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyesyes
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 indexesrestrictednoyesno
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardnoyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
in-process shared libraryADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin PythonnoTransact SQLno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding, horizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyesnone
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 integrityyes infoinformational only, not enforced by the systemno infotypically not needed, however similar functionality with collection joins possibleno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes
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 controlfine grained access rights according to SQL-standardnoyesno

More information provided by the system vendor

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3rd partiesSQLFlow: Provides a visual representation of the overall flow of data. Automated SQL data lineage analysis across Databases, ETL, Business Intelligence, Cloud and Hadoop environments by parsing SQL Script and stored procedure.
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SQLFlow: Provides a visual representation of the overall flow of data. Automated SQL data lineage analysis across Databases, ETL, Business Intelligence, Cloud and Hadoop environments by parsing SQL Script and stored procedure.
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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon RedshiftEJDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQL
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