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DBMS > GigaSpaces vs. LeanXcale vs. Solr vs. Splice Machine

System Properties Comparison GigaSpaces vs. LeanXcale vs. Solr vs. Splice Machine

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Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonLeanXcale  Xexclude from comparisonSolr  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesA widely used distributed, scalable search engine based on Apache LuceneOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Key-value store
Relational DBMS
Search engineRelational DBMS
Secondary database modelsGraph DBMS
Search engine
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.gigaspaces.comwww.leanxcale.comsolr.apache.orgsplicemachine.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlsolr.apache.org/­resources.htmlsplicemachine.com/­how-it-works
DeveloperGigaspaces TechnologiesLeanXcaleApache Software FoundationSplice Machine
Initial release2000201520062014
Current release15.5, September 20209.6.1, May 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoApache Version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJavaJava
Server operating systemsLinux
macOS
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyes
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 metadatayes
Secondary indexesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLSQL-99 for query and DML statementsyes infothrough Apache DerbySolr Parallel SQL Interfaceyes
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Java API
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C++
Java
Python
Scala
C
Java
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesJava pluginsyes infoJava
Triggersyes, event driven architectureyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes
User concepts infoAccess controlRole-based access controlyesAccess rights for users, groups and roles according to SQL-standard

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More resources
GigaSpacesLeanXcaleSolrSplice Machine
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