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DBMS > Geode vs. Spark SQL vs. Trafodion vs. Ultipa

System Properties Comparison Geode vs. Spark SQL vs. Trafodion vs. Ultipa

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Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparisonUltipa  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMSHigh performance Graph DBMS supporting HTAP high availability cluster deployment
Primary database modelKey-value storeRelational DBMSRelational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.86
Rank#134  Overall
#24  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.19
Rank#330  Overall
#30  Graph DBMS
Websitegeode.apache.orgspark.apache.org/­sqltrafodion.apache.orgwww.ultipa.com
Technical documentationgeode.apache.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.htmlwww.ultipa.com/­document
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Apache Software FoundationApache Software Foundation, originally developed by HPUltipa
Initial release2002201420142019
Current release1.1, February 20173.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++, Java
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredLinux
OS X
Windows
Linux
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonono
Secondary indexesnonoyes
SQL infoSupport of SQLSQL-like query language (OQL)SQL-like DML and DDL statementsyes
APIs and other access methodsJava Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.NetC++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsnoJava Stored Procedures
Triggersyes infoCache Event Listenersnono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes, on a single nodenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights per client and object definablenofine grained access rights according to SQL-standard

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More resources
GeodeSpark SQLTrafodionUltipa
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