DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon DynamoDB vs. Google Cloud Bigtable vs. OpenQM vs. Yaacomo

System Properties Comparison Amazon DynamoDB vs. Google Cloud Bigtable vs. OpenQM vs. Yaacomo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
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.QpenQM is a high-performance, self-tuning, multi-value DBMSOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Key-value store
Key-value store
Wide column store
Multivalue DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.45
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.34
Rank#284  Overall
#10  Multivalue DBMS
Websiteaws.amazon.com/­dynamodbcloud.google.com/­bigtablewww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qmyaacomo.com
Technical documentationdocs.aws.amazon.com/­dynamodbcloud.google.com/­bigtable/­docs
DeveloperAmazonGoogleRocket Software, originally Martin PhillipsQ2WEB GmbH
Initial release2012201519932009
Current release3.4-12
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialOpen Source infoGPLv2, extended commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Server operating systemshostedhostedAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Android
Linux
Windows
Data schemeschema-freeschema-freeyes infowith some exceptionsyes
Typing infopredefined data types such as float or dateyesnoyes
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
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnononoyes
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Basic
C
Java
Objective C
PHP
Python
Server-side scripts infoStored proceduresnonoyes
Triggersyes infoby integration with AWS Lambdanoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyeshorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesnono
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)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
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 operationsACIDACID
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.noyes
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)Access rights can be defined down to the item levelfine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon DynamoDBGoogle Cloud BigtableOpenQM infoalso called QMYaacomo
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Increased popularity for consuming DBMS services out of the cloud
2 October 2015, Paul Andlinger

show all

Recent citations in the news

Use Amazon DynamoDB incremental exports to drive continuous data retention | Amazon Web Services
12 June 2024, AWS Blog

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

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

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

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

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

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

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

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here