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DBMS > GigaSpaces vs. InfinityDB vs. IRONdb vs. Spark SQL vs. Trafodion

System Properties Comparison GigaSpaces vs. InfinityDB vs. IRONdb vs. Spark SQL vs. Trafodion

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonInfinityDB  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.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 TransactionsA Java embedded Key-Value Store which extends the Java Map interfaceA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicitySpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Key-value storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
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
Score0.00
Rank#378  Overall
#57  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.gigaspaces.comboilerbay.comwww.circonus.com/solutions/time-series-database/spark.apache.org/­sqltrafodion.apache.org
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlboilerbay.com/­infinitydb/­manualdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperGigaspaces TechnologiesBoiler Bay Inc.Circonus LLC.Apache Software FoundationApache Software Foundation, originally developed by HP
Initial release20002002201720142014
Current release15.5, September 20204.0V0.10.20, January 20183.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJavaC and C++ScalaC++, Java
Server operating systemsLinux
macOS
Solaris
Windows
All OS with a Java VMLinuxLinux
OS X
Windows
Linux
Data schemeschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes infotext, numeric, histogramsyesyes
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 metadatanononono
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilitynonoyes
SQL infoSupport of SQLSQL-99 for query and DML statementsnoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsyes
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languages.Net
C++
Java
Python
Scala
Java.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyesnoyes, in LuanoJava Stored Procedures
Triggersyes, event driven architecturenononono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneAutomatic, metric affinity per nodeyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
noneconfigurable replication factor, datacenter awarenoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnonoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilitynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnononono
User concepts infoAccess controlRole-based access controlnononofine grained access rights according to SQL-standard

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More resources
GigaSpacesInfinityDBIRONdbSpark SQLTrafodion
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