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DBMS > Ignite vs. Solr vs. Spark SQL vs. Splice Machine

System Properties Comparison Ignite vs. Solr vs. Spark SQL vs. Splice Machine

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Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value store
Relational DBMS
Search engineRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteignite.apache.orgsolr.apache.orgspark.apache.org/­sqlsplicemachine.com
Technical documentationapacheignite.readme.io/­docssolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperApache Software FoundationApache Software FoundationApache Software FoundationSplice Machine
Initial release2015200620142014
Current releaseApache Ignite 2.69.6.0, April 20243.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2Open Source infoApache 2.0Open 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 languageC++, Java, .NetJavaScalaJava
Server operating systemsLinux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyesyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyesyes
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.yesyesno
Secondary indexesyesyes infoAll search fields are automatically indexednoyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSolr Parallel SQL InterfaceSQL-like DML and DDL statementsyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)Java pluginsnoyes infoJava
Triggersyes (cache interceptors and events)yes infoUser configurable commands triggered on index changesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)spark-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 ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingnoACID
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.yesyesnoyes
User concepts infoAccess controlSecurity Hooks for custom implementationsyesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
IgniteSolrSpark SQLSplice Machine
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