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DBMS > GigaSpaces vs. Kinetica vs. LeanXcale

System Properties Comparison GigaSpaces vs. Kinetica vs. LeanXcale

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Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonKinetica  Xexclude from comparisonLeanXcale  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsFully vectorized database across both GPUs and CPUsA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMSKey-value store
Relational DBMS
Secondary database modelsGraph DBMS
Search engine
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.02
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.35
Rank#283  Overall
#41  Key-value stores
#128  Relational DBMS
Websitewww.gigaspaces.comwww.kinetica.comwww.leanxcale.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.kinetica.com
DeveloperGigaspaces TechnologiesKineticaLeanXcale
Initial release200020122015
Current release15.5, September 20207.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC, C++
Server operating systemsLinux
macOS
Solaris
Windows
Linux
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes
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
Secondary indexesyesyes
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL-like DML and DDL statementsyes infothrough Apache Derby
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Supported programming languages.Net
C++
Java
Python
Scala
C++
Java
JavaScript (Node.js)
Python
C
Java
Scala
Server-side scripts infoStored proceduresyesuser defined functions
Triggersyes, event driven architectureyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlRole-based access controlAccess rights for users and roles on table level

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More resources
GigaSpacesKineticaLeanXcale
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