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DBMS > Ignite vs. Spark SQL vs. Trafodion

System Properties Comparison Ignite vs. Spark SQL vs. Trafodion

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Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  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 processingTransactional SQL-on-Hadoop DBMS
Primary database modelKey-value store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.16
Rank#83  Overall
#10  Key-value stores
#44  Relational DBMS
Score20.07
Rank#35  Overall
#21  Relational DBMS
Score0.70
Rank#270  Overall
#121  Relational DBMS
Websiteignite.apache.orgspark.apache.org/­sqltrafodion.apache.org
Technical documentationapacheignite.readme.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org
DeveloperApache Software FoundationApache Software FoundationApache Software Foundation, originally developed by HP
Initial release201520142014
Current releaseApache Ignite 2.63.4.0 ( 2.13), April 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetScalaC++, Java
Server operating systemsLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux
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.yesnono
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
ADO.NET
JDBC
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)noJava Stored Procedures
Triggersyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)noneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yes infovia user defined functions and HBase
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
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.yesnono
User concepts infoAccess controlSecurity Hooks for custom implementationsnofine grained access rights according to SQL-standard

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More resources
IgniteSpark SQLTrafodion
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