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DBMS > GigaSpaces vs. Ingres vs. Spark SQL vs. Splice Machine vs. Trafodion

System Properties Comparison GigaSpaces vs. Ingres vs. Spark SQL vs. Splice Machine vs. Trafodion

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonIngres  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. 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 TransactionsWell established RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTransactional SQL-on-Hadoop DBMS
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.gigaspaces.comwww.actian.com/­databases/­ingresspark.apache.org/­sqlsplicemachine.comtrafodion.apache.org
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.actian.com/­ingresspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-workstrafodion.apache.org/­documentation.html
DeveloperGigaspaces TechnologiesActian CorporationApache Software FoundationSplice MachineApache Software Foundation, originally developed by HP
Initial release20001974 infooriginally developed at University Berkely in early 1970s201420142014
Current release15.5, September 202011.2, May 20223.5.0 ( 2.13), September 20233.1, March 20212.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetCScalaJavaC++, Java
Server operating systemsLinux
macOS
Solaris
Windows
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 metadatano infobut tools for importing/exporting data from/to XML-files availablenono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-99 for query and DML statementsyesSQL-like DML and DDL statementsyesyes
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
Supported programming languages.Net
C++
Java
Python
Scala
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyesyesnoyes infoJavaJava Stored Procedures
Triggersyes, event driven architectureyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslyyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Ingres ReplicatornoneMulti-source replication
Source-replica replication
yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnoYes, via Full Spark Integrationyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesno
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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GigaSpacesIngresSpark SQLSplice MachineTrafodion
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