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DBMS > Ignite vs. Spark SQL vs. Splice Machine

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

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Editorial information provided by DB-Engines
NameIgnite  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.Spark 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
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.41
Rank#69  Overall
#9  Key-value stores
#38  Relational DBMS
Score22.94
Rank#34  Overall
#20  Relational DBMS
Score0.79
Rank#197  Overall
#97  Relational DBMS
Websiteignite.apache.orgspark.apache.org/­sqlsplicemachine.com
Technical documentationapacheignite.readme.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldoc.splicemachine.com
DeveloperApache Software FoundationApache Software FoundationSplice Machine
Initial release201520142014
Current releaseApache Ignite 2.63.1.1, March 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetScalaJava
Server operating systemsLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyes
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.yesno
Secondary indexesyesnoyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Java
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)noyes infoJava
Triggersyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)Yes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
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.yesnoyes
User concepts infoAccess controlSecurity Hooks for custom implementationsnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
IgniteSpark SQLSplice Machine
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More resources
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