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DBMS > Ignite vs. Netezza vs. RRDtool vs. Spark SQL vs. Splice Machine

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

Editorial information provided by DB-Engines
NameIgnite  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonRRDtool  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.Data warehouse and analytics appliance part of IBM PureSystemsIndustry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database. infoThe data is stored in a circular buffer, thus the system storage footprint remains constant over time.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 DBMSTime Series DBMSRelational DBMSRelational 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
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score1.87
Rank#136  Overall
#11  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteignite.apache.orgwww.ibm.com/­products/­netezzaoss.oetiker.ch/­rrdtoolspark.apache.org/­sqlsplicemachine.com
Technical documentationapacheignite.readme.io/­docsoss.oetiker.ch/­rrdtool/­docspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperApache Software FoundationIBMTobias OetikerApache Software FoundationSplice Machine
Initial release20152000199920142014
Current releaseApache Ignite 2.61.8.0, 20223.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoGPL V2 and FLOSSOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetC infoImplementations in Java (e.g. RRD4J) and C# availableScalaJava
Server operating systemsLinux
OS X
Solaris
Windows
Linux infoincluded in applianceHP-UX
Linux
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data onlyyesyes
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 infoExporting into and restoring from XML files possibleno
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLyesnoSQL-like DML and DDL statementsyes
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
OLE DB
in-process shared library
Pipes
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
C infowith librrd library
C# infowith a different implementation of RRDTool
Java infowith a different implementation of RRDTool
JavaScript (Node.js) infowith a different implementation of RRDTool
Lua
Perl
PHP infowith a wrapper library
Python
Ruby
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)yesnonoyes infoJava
Triggersyes (cache interceptors and events)nononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Source-replica replicationnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoby using the rrdcached daemonyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
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 implementationsUsers with fine-grained authorization conceptnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
IgniteNetezza infoAlso called PureData System for Analytics by IBMRRDtoolSpark SQLSplice Machine
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