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DBMS > EXASOL vs. Geode vs. Interbase vs. Kinetica vs. Splice Machine

System Properties Comparison EXASOL vs. Geode vs. Interbase vs. Kinetica vs. Splice Machine

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGeode  Xexclude from comparisonInterbase  Xexclude from comparisonKinetica  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesLight-weight proven RDBMS infooriginally from BorlandFully vectorized database across both GPUs and CPUsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score1.86
Rank#134  Overall
#24  Key-value stores
Score4.08
Rank#75  Overall
#41  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.exasol.comgeode.apache.orgwww.embarcadero.com/­products/­interbasewww.kinetica.comsplicemachine.com
Technical documentationwww.exasol.com/­resourcesgeode.apache.org/­docsdocs.embarcadero.com/­products/­interbasedocs.kinetica.comsplicemachine.com/­how-it-works
DeveloperExasolOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.EmbarcaderoKineticaSplice Machine
Initial release20002002198420122014
Current release1.1, February 2017InterBase 2020, December 20197.1, August 20213.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses available as GemfirecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
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 languageJavaCC, C++Java
Server operating systemsAll OS with a Java VM infothe JDK (8 or later) is also requiredAndroid
iOS
Linux
OS X
Windows
LinuxLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesyes
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.nonono infoexport as XML data possibleno
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLyesSQL-like query language (OQL)yesSQL-like DML and DDL statementsyes
APIs and other access methods.Net
JDBC
ODBC
WebSocket
Java Client API
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJava
Lua
Python
R
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
C++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsyes infoInterbase procedure and trigger languageuser defined functionsyes infoJava
Triggersyesyes infoCache Event Listenersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationInterbase Change ViewsSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes, on a single nodeACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMultiversion concurreny controlyesyes, multi-version concurrency control (MVCC)
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.yesyesyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights per client and object definablefine grained access rights according to SQL-standardAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standard

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More resources
EXASOLGeodeInterbaseKineticaSplice Machine
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