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DBMS > EsgynDB vs. Google Cloud Bigtable vs. IBM Db2 warehouse vs. Kdb vs. Netezza

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. IBM Db2 warehouse vs. Kdb vs. Netezza

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonKdb  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Cloud-based data warehousing serviceHigh performance Time Series DBMSData warehouse and analytics appliance part of IBM PureSystems
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSTime Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score1.30
Rank#164  Overall
#75  Relational DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablewww.ibm.com/­products/­db2/­warehousekx.comwww.ibm.com/­products/­netezza
Technical documentationcloud.google.com/­bigtable/­docscode.kx.com
DeveloperEsgynGoogleIBMKx Systems, a division of First Derivatives plcIBM
Initial release2015201520142000 infokdb was released 2000, kdb+ in 20032000
Current release3.6, May 2018
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infofree 32-bit versioncommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, Javaq
Server operating systemsLinuxhostedhostedLinux
OS X
Solaris
Windows
Linux infoincluded in appliance
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nonono infoImport/export of XML data possibleyes
Secondary indexesyesnoyesyes infotable attribute 'grouped'yes
SQL infoSupport of SQLyesnoyesSQL-like query language (q)yes
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
.NET Client API
JDBC
ODBC
OLE DB
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresJava Stored ProceduresnoPL/SQL, SQL PLuser defined functionsyes
Triggersnonoyesyes infowith viewsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyesSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono infosimilar paradigm used for internal processingyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardrights management via user accountsUsers with fine-grained authorization concept
More information provided by the system vendor
EsgynDBGoogle Cloud BigtableIBM Db2 warehouse infoformerly named IBM dashDBKdbNetezza infoAlso called PureData System for Analytics by IBM
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
EsgynDBGoogle Cloud BigtableIBM Db2 warehouse infoformerly named IBM dashDBKdbNetezza infoAlso called PureData System for Analytics by IBM
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