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DBMS > Citus vs. EsgynDB vs. Google Cloud Spanner vs. Hyprcubd vs. Netezza

System Properties Comparison Citus vs. EsgynDB vs. Google Cloud Spanner vs. Hyprcubd vs. Netezza

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHyprcubd  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Serverless Time Series DBMSData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score8.59
Rank#45  Overall
#29  Relational DBMS
Websitewww.citusdata.comwww.esgyn.cncloud.google.com/­spannerhyprcubd.com (offline)www.ibm.com/­products/­netezza
Technical documentationdocs.citusdata.comcloud.google.com/­spanner/­docs
DeveloperEsgynGoogleHyprcubd, Inc.IBM
Initial release2010201520172000
Current release8.1, December 2018
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++, JavaGo
Server operating systemsLinuxLinuxhostedhostedLinux infoincluded in appliance
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infotime, int, uint, float, stringyes
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.yes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsyesyes infoQuery statements complying to ANSI 2011SQL-like query languageyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
gRPC (https)JDBC
ODBC
OLE DB
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
All languages supporting JDBC/ODBC/ADO.NetGo
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Java Stored Proceduresnonoyes
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication between multi datacentersMulti-source replication with 3 replicas for regional instances.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infousing Google Cloud Dataflownoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoStrict serializable isolationnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesnoyes
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.nononono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)token accessUsers with fine-grained authorization concept

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More resources
CitusEsgynDBGoogle Cloud SpannerHyprcubdNetezza infoAlso called PureData System for Analytics by IBM
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