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DBMS > GridGain vs. Microsoft Azure Synapse Analytics vs. Postgres-XL vs. Quasardb

System Properties Comparison GridGain vs. Microsoft Azure Synapse Analytics vs. Postgres-XL vs. Quasardb

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonPostgres-XL  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresDistributed, high-performance timeseries database
Primary database modelColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score18.98
Rank#31  Overall
#19  Relational DBMS
Score0.43
Rank#260  Overall
#119  Relational DBMS
Score0.13
Rank#332  Overall
#28  Time Series DBMS
Websitewww.gridgain.comazure.microsoft.com/­services/­synapse-analyticswww.postgres-xl.orgquasar.ai
Technical documentationwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­azure/­synapse-analyticswww.postgres-xl.org/­documentationdoc.quasar.ai/­master
DeveloperGridGain Systems, Inc.Microsoftquasardb
Initial release200720162014 infosince 2012, originally named StormDB2009
Current releaseGridGain 8.5.110 R1, October 20183.14.1, January 2024
License infoCommercial or Open Sourcecommercial, open sourcecommercialOpen Source infoMozilla public licensecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .Net, Python, REST, SQLC++CC++
Server operating systemsLinux
OS X
Solaris
Windows
z/OS
hostedLinux
macOS
BSD
Linux
OS X
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binary
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.yesnoyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesyes infowith tags
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLyesyes infodistributed, parallel query executionSQL-like query language
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C#
Java
PHP
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)Transact SQLuser defined functionsno
Triggersyes (cache interceptors and events)noyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioninghorizontal partitioningSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yesSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nonowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoTransient mode
User concepts infoAccess controlRole-based access control
Security Hooks for custom implementations
yesfine grained access rights according to SQL-standardCryptographically strong user authentication and audit trail

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More resources
GridGainMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehousePostgres-XLQuasardb
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