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DBMS > Google Cloud Datastore vs. LevelDB vs. Microsoft Azure Table Storage vs. Riak KV

System Properties Comparison Google Cloud Datastore vs. LevelDB vs. Microsoft Azure Table Storage vs. Riak KV

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesA Wide Column Store for rapid development using massive semi-structured datasetsDistributed, fault tolerant key-value store
Primary database modelDocument storeKey-value storeWide column 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
Score4.36
Rank#72  Overall
#12  Document stores
Score2.25
Rank#115  Overall
#19  Key-value stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Score4.01
Rank#79  Overall
#9  Key-value stores
Websitecloud.google.com/­datastoregithub.com/­google/­leveldbazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationcloud.google.com/­datastore/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperGoogleGoogleMicrosoftOpenSource, formerly Basho Technologies
Initial release2008201120122009
Current release1.23, February 20213.2.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoBSDcommercialOpen 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 systemshostedIllumos
Linux
OS X
Windows
hostedLinux
OS X
Data schemeschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyes, details herenoyesno
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.nononono
Secondary indexesyesnonorestricted
SQL infoSupport of SQLSQL-like query language (GQL)nonono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP APIHTTP API
Native Erlang Interface
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C#
C++
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 proceduresusing Google App EnginenonoErlang
TriggersCallbacks using the Google Apps Enginenonoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud serviceSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosnoneyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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.Immediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnooptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyesyes
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, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights based on private key authentication or shared access signaturesyes, using Riak Security

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More resources
Google Cloud DatastoreLevelDBMicrosoft Azure Table StorageRiak KV
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