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DBMS > Google Cloud Bigtable vs. Ignite vs. Netezza vs. Stardog

System Properties Comparison Google Cloud Bigtable vs. Ignite vs. Netezza vs. Stardog

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonIgnite  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonStardog  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.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Data warehouse and analytics appliance part of IBM PureSystemsEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelKey-value store
Wide column store
Key-value store
Relational DBMS
Relational DBMSGraph DBMS
RDF store
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
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitecloud.google.com/­bigtableignite.apache.orgwww.ibm.com/­products/­netezzawww.stardog.com
Technical documentationcloud.google.com/­bigtable/­docsapacheignite.readme.io/­docsdocs.stardog.com
DeveloperGoogleApache Software FoundationIBMStardog-Union
Initial release2015201520002010
Current releaseApache Ignite 2.67.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, Java, .NetJava
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux infoincluded in applianceLinux
macOS
Windows
Data schemeschema-freeyesyesschema-free and OWL/RDFS-schema support
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.noyesno infoImport/export of XML data possible
Secondary indexesnoyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLyesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
OLE DB
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)yesuser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes (cache interceptors and events)noyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes (replicated cache)Source-replica replicationMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)yesno
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 in HA-Cluster
Foreign keys infoReferential integritynononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACIDACID
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Security Hooks for custom implementationsUsers with fine-grained authorization conceptAccess rights for users and roles

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More resources
Google Cloud BigtableIgniteNetezza infoAlso called PureData System for Analytics by IBMStardog
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31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
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Google scales up Cloud Bigtable NoSQL database
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Google Cloud makes it cheaper to run smaller workloads on Bigtable
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14 May 2016, AWS Blog

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1 June 2023, Datanami

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IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

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