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

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

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionData 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 modelRelational DBMSRelational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.06
Rank#365  Overall
#55  Key-value stores
Websitewww.esgyn.cnwww.ibm.com/­products/­netezzaspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynIBMApache Software FoundationSTS Soft SC
Initial release2015200020142011
Current release3.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourcecommercialcommercialOpen 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 languageC++, JavaScalaC#
Server operating systemsLinuxLinux infoincluded in applianceLinux
OS X
Windows
Windows
Data schemeyesyesyesyes
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 indexesyesyesnono
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
OLE DB
JDBC
ODBC
.NET Client API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C#
Java
Server-side scripts infoStored proceduresJava Stored Proceduresyesnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
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 controlfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptnono

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