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DBMS > GigaSpaces vs. Microsoft Azure Synapse Analytics vs. Spark SQL

System Properties Comparison GigaSpaces vs. Microsoft Azure Synapse Analytics vs. Spark SQL

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Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsElastic, 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 modelDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.52
Rank#171  Overall
#29  Document stores
#8  Object oriented DBMS
Score21.94
Rank#33  Overall
#19  Relational DBMS
Score20.15
Rank#36  Overall
#22  Relational DBMS
Websitewww.gigaspaces.comazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sql
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGigaspaces TechnologiesMicrosoftApache Software Foundation
Initial release200020162014
Current release15.5, September 20203.3.0 ( 2.13), June 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetC++Scala
Server operating systemsLinux
macOS
Solaris
Windows
hostedLinux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.no infoXML can be used for describing objects metadatanono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-99 for query and DML statementsyesSQL-like DML and DDL statements
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languages.Net
C++
Java
Python
Scala
C#
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesTransact SQLno
Triggersyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency
Foreign keys infoReferential integritynono 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 dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlRole-based access controlyesno

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More resources
GigaSpacesMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQL
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