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DBMS > Netezza vs. Spark SQL vs. Sphinx vs. XTDB

System Properties Comparison Netezza vs. Spark SQL vs. Sphinx vs. XTDB

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Editorial information provided by DB-Engines
NameNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databasesA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelRelational DBMSRelational DBMSSearch engineDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.11
Rank#343  Overall
#46  Document stores
Websitewww.ibm.com/­products/­netezzaspark.apache.org/­sqlsphinxsearch.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docswww.xtdb.com/­docs
DeveloperIBMApache Software FoundationSphinx Technologies Inc.Juxt Ltd.
Initial release2000201420012019
Current release3.5.0 ( 2.13), September 20233.5.1, February 20231.19, September 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++Clojure
Server operating systemsLinux infoincluded in applianceLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyes, extensible-data-notation format
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 indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like query language (SphinxQL)limited SQL, making use of Apache Calcite
APIs and other access methodsJDBC
ODBC
OLE DB
JDBC
ODBC
Proprietary protocolHTTP REST
JDBC
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Clojure
Java
Server-side scripts infoStored proceduresyesnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnonenoneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlUsers with fine-grained authorization conceptnono

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More resources
Netezza infoAlso called PureData System for Analytics by IBMSpark SQLSphinxXTDB infoformerly named Crux
DB-Engines blog posts

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4 February 2013, Paul Andlinger

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