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DBMS > Heroic vs. Netezza vs. Spark SQL vs. STSdb

System Properties Comparison Heroic vs. Netezza vs. Spark SQL vs. STSdb

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelTime Series DBMSRelational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitegithub.com/­spotify/­heroicwww.ibm.com/­products/­netezzaspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationspotify.github.io/­heroicspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperSpotifyIBMApache Software FoundationSTS Soft SC
Initial release2014200020142011
Current release3.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0Open Source infoGPLv2, 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 languageJavaScalaC#
Server operating systemsLinux infoincluded in applianceLinux
OS X
Windows
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infoprimitive types and user defined types (classes)
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.nono
Secondary indexesyes infovia Elasticsearchyesnono
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsno
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
ODBC
OLE DB
JDBC
ODBC
.NET Client API
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresnoyesnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nono
User concepts infoAccess controlUsers with fine-grained authorization conceptnono

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More resources
HeroicNetezza infoAlso called PureData System for Analytics by IBMSpark SQLSTSdb
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