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DBMS > Amazon DynamoDB vs. Google Cloud Bigtable vs. KairosDB vs. Netezza

System Properties Comparison Amazon DynamoDB vs. Google Cloud Bigtable vs. KairosDB vs. Netezza

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKairosDB  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Distributed Time Series DBMS based on Cassandra or H2Data warehouse and analytics appliance part of IBM PureSystems
Primary database modelDocument store
Key-value store
Key-value store
Wide column store
Time Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score77.57
Rank#16  Overall
#2  Document stores
#2  Key-value stores
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score0.71
Rank#230  Overall
#20  Time Series DBMS
Score10.18
Rank#46  Overall
#29  Relational DBMS
Websiteaws.amazon.com/­dynamodbcloud.google.com/­bigtablegithub.com/­kairosdb/­kairosdbwww.ibm.com/­products/­netezza
Technical documentationdocs.aws.amazon.com/­dynamodbcloud.google.com/­bigtable/­docskairosdb.github.io
DeveloperAmazonGoogleIBM
Initial release2012201520132000
Current release1.2.2, November 2018
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemshostedhostedLinux
OS X
Windows
Linux infoincluded in appliance
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesyesnonoyes
SQL infoSupport of SQLnononoyes
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Graphite protocol
HTTP REST
Telnet API
JDBC
ODBC
OLE DB
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
Java
JavaScript infoNode.js
PHP
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Server-side scripts infoStored proceduresnononoyes
Triggersyes infoby integration with AWS Lambdanonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor infobased on CassandraSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionAtomic single-row operationsnoACID
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.nono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access controlUsers with fine-grained authorization concept

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More resources
Amazon DynamoDBGoogle Cloud BigtableKairosDBNetezza infoAlso called PureData System for Analytics by IBM
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Recent citations in the news

AWS announces Amazon DynamoDB zero-ETL integration with Amazon OpenSearch Service
28 November 2023, AWS Blog

Simplify cross-account access control with Amazon DynamoDB using resource-based policies | Amazon Web Services
20 March 2024, AWS Blog

A new and improved AWS CDK construct for Amazon DynamoDB tables | Amazon Web Services
31 January 2024, AWS Blog

Bulk update Amazon DynamoDB tables with AWS Step Functions | Amazon Web Services
20 March 2024, AWS Blog

Simplify private connectivity to Amazon DynamoDB with AWS PrivateLink | Amazon Web Services
19 March 2024, AWS Blog

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Google's AI-First Strategy Brings Vector Support To Cloud Databases
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1 March 2022, TechTarget

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

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Expo: Real Time A/B Testing and Monitoring with Spark Streaming and Kafka at Walmart Labs
24 May 2019, InfoQ.com

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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.com

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

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
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