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DBMS > Geode vs. Spark SQL vs. Transbase

System Properties Comparison Geode vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameGeode  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
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 processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#134  Overall
#26  Key-value stores
Score22.86
Rank#35  Overall
#21  Relational DBMS
Score0.07
Rank#325  Overall
#147  Relational DBMS
Websitegeode.apache.orgspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationgeode.apache.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Apache Software FoundationTransaction Software GmbH
Initial release200220141987
Current release1.1, February 20173.2.0, October 2021Transbase 8.4, September 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC and C++
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
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
Proprietary native API
Supported programming languages.Net
All JVM based languages
C++
Groovy
Java
Scala
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsnoyes
Triggersyes infoCache Event Listenersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
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 nodenoyes
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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GeodeSpark SQLTransbase
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