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DBMS > Google Cloud Bigtable vs. InterSystems IRIS vs. Netezza vs. Splice Machine

System Properties Comparison Google Cloud Bigtable vs. InterSystems IRIS vs. Netezza vs. Splice Machine

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityData warehouse and analytics appliance part of IBM PureSystemsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value store
Wide column store
Document store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.05
Rank#83  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitecloud.google.com/­bigtablewww.intersystems.com/­products/­intersystems-iriswww.ibm.com/­products/­netezzasplicemachine.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clssplicemachine.com/­how-it-works
DeveloperGoogleInterSystemsIBMSplice Machine
Initial release2015201820002014
Current release2023.3, June 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemshostedAIX
Linux
macOS
Ubuntu
Windows
Linux infoincluded in applianceLinux
OS X
Solaris
Windows
Data schemeschema-freedepending on used data modelyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.noyes
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyesyesyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C++
Java
JavaScript (Node.js)
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesyesyes infoJava
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesUsers with fine-grained authorization conceptAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Google Cloud BigtableInterSystems IRISNetezza infoAlso called PureData System for Analytics by IBMSplice Machine
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources
Google Cloud BigtableInterSystems IRISNetezza infoAlso called PureData System for Analytics by IBMSplice Machine
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