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DBMS > Amazon SimpleDB vs. Google Cloud Datastore vs. LevelDB vs. Sphinx

System Properties Comparison Amazon SimpleDB vs. Google Cloud Datastore vs. LevelDB vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonLevelDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreAutomatically 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 valuesOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value storeDocument storeKey-value storeSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
Score2.35
Rank#111  Overall
#19  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­simpledbcloud.google.com/­datastoregithub.com/­google/­leveldbsphinxsearch.com
Technical documentationdocs.aws.amazon.com/­simpledbcloud.google.com/­datastore/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdsphinxsearch.com/­docs
DeveloperAmazonGoogleGoogleSphinx Technologies Inc.
Initial release2007200820112001
Current release1.23, February 20213.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDOpen Source infoGPL version 2, commercial licence available
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.
Implementation languageC++C++
Server operating systemshostedhostedIllumos
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyes, details herenono
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 indexesyes infoAll columns are indexed automaticallyyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query language (GQL)noSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
.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
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnousing Google App Enginenono
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
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.Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes infoThe original contents of fields are not stored in the Sphinx index.
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)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nono

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More resources
Amazon SimpleDBGoogle Cloud DatastoreLevelDBSphinx
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