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DBMS > GridGain vs. Microsoft Azure Synapse Analytics vs. Oracle Berkeley DB vs. SiteWhere

System Properties Comparison GridGain vs. Microsoft Azure Synapse Analytics vs. Oracle Berkeley DB vs. SiteWhere

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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 comparisonOracle Berkeley DB  Xexclude from comparisonSiteWhere  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 ServerWidely used in-process key-value storeM2M integration platform for persisting/querying time series data
Primary database modelColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Time Series 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
Score1.88
Rank#130  Overall
#23  Key-value stores
#3  Native XML DBMS
Score0.07
Rank#347  Overall
#33  Time Series DBMS
Websitewww.gridgain.comazure.microsoft.com/­services/­synapse-analyticswww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlgithub.com/­sitewhere/­sitewhere
Technical documentationwww.gridgain.com/­docs/­index.htmldocs.microsoft.com/­azure/­synapse-analyticsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsitewhere1.sitewhere.io/­index.html
DeveloperGridGain Systems, Inc.MicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleSiteWhere
Initial release2007201619942010
Current releaseGridGain 8.5.118.1.40, May 2020
License infoCommercial or Open Sourcecommercial, open sourcecommercialOpen Source infocommercial license availableOpen Source infoCommon Public Attribution License Version 1.0
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++C, Java, C++ (depending on the Berkeley DB edition)Java
Server operating systemsLinux
OS X
Solaris
Windows
z/OS
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Data schemeyesyesschema-freepredefined scheme
Typing infopredefined data types such as float or dateyesyesnoyes
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 infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesyesno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLyesyes infoSQL interfaced based on SQLite is availableno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
HTTP REST
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C#
Java
PHP
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)Transact SQLno
Triggersyes (cache interceptors and events)noyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesShardingSharding, horizontal partitioningnoneSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yesSource-replica replicationselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.yesyesno
User concepts infoAccess controlRole-based access control
Security Hooks for custom implementations
yesnoUsers with fine-grained authorization concept

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More resources
GridGainMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseOracle Berkeley DBSiteWhere
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