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DBMS > Amazon DynamoDB vs. Drizzle vs. Google Cloud Datastore vs. Riak KV

System Properties Comparison Amazon DynamoDB vs. Drizzle vs. Google Cloud Datastore vs. Riak KV

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonRiak KV  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDistributed, fault tolerant key-value store
Primary database modelDocument store
Key-value store
Relational DBMSDocument storeKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score79.85
Rank#16  Overall
#2  Document stores
#2  Key-value stores
Score4.84
Rank#76  Overall
#11  Document stores
Score6.09
Rank#64  Overall
#7  Key-value stores
Websiteaws.amazon.com/­dynamodbcloud.google.com/­datastoreriak.com/­products/­riak-kv
Technical documentationdocs.aws.amazon.com/­dynamodbcloud.google.com/­datastore/­docs
DeveloperAmazonDrizzle project, originally started by Brian AkerGoogleBasho Technologies
Initial release2012200820082009
Current release7.2.4, September 20122.1.0, April 2015
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoGNU GPLcommercialOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Erlang
Server operating systemshostedFreeBSD
Linux
OS X
hostedLinux
OS X
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes, details hereno
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 indexesyesyesyesrestricted
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL-like query language (GQL)no
APIs and other access methodsRESTful HTTP APIJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
Native Erlang Interface
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresnonousing Google App EngineJavaScript and Erlang
Triggersyes infoby integration with AWS Lambdano infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Engineyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replication using Paxosselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsno infolinks between data sets can be stored
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 regionACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
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.no
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Pluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Amazon DynamoDBDrizzleGoogle Cloud DatastoreRiak KV
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