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DBMS > GigaSpaces vs. IRONdb vs. Kinetica vs. Microsoft Azure Synapse Analytics vs. RDF4J

System Properties Comparison GigaSpaces vs. IRONdb vs. Kinetica vs. Microsoft Azure Synapse Analytics vs. RDF4J

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully vectorized database across both GPUs and CPUsElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSRelational DBMSRelational DBMSRDF store
Secondary database modelsGraph DBMS
Search engine
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websitewww.gigaspaces.comwww.circonus.com/solutions/time-series-database/www.kinetica.comazure.microsoft.com/­services/­synapse-analyticsrdf4j.org
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.circonus.com/irondb/category/getting-starteddocs.kinetica.comdocs.microsoft.com/­azure/­synapse-analyticsrdf4j.org/­documentation
DeveloperGigaspaces TechnologiesCirconus LLC.KineticaMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20002017201220162004
Current release15.5, September 2020V0.10.20, January 20187.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC and C++C, C++C++Java
Server operating systemsLinux
macOS
Solaris
Windows
LinuxLinuxhostedLinux
OS X
Unix
Windows
Data schemeschema-freeschema-freeyesyesyes infoRDF Schemas
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyesyes
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 metadatanonono
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsyesno
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP APIJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languages.Net
C++
Java
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
C#
Java
PHP
Java
PHP
Python
Server-side scripts infoStored proceduresyesyes, in Luauser defined functionsTransact SQLyes
Triggersyes, event driven architecturenoyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeShardingSharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
configurable replication factor, datacenter awareSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoGPU vRAM or System RAM
User concepts infoAccess controlRole-based access controlnoAccess rights for users and roles on table levelyesno

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More resources
GigaSpacesIRONdbKineticaMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRDF4J infoformerly known as Sesame
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