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DBMS > Amazon SimpleDB vs. Google Cloud Datastore vs. Spark SQL vs. TimesTen

System Properties Comparison Amazon SimpleDB vs. Google Cloud Datastore vs. Spark SQL vs. TimesTen

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSpark SQL  Xexclude from comparisonTimesTen  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 PlatformSpark SQL is a component on top of 'Spark Core' for structured data processingIn-Memory RDBMS compatible to Oracle
Primary database modelKey-value storeDocument storeRelational DBMSRelational DBMS
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
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.31
Rank#163  Overall
#74  Relational DBMS
Websiteaws.amazon.com/­simpledbcloud.google.com/­datastorespark.apache.org/­sqlwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.aws.amazon.com/­simpledbcloud.google.com/­datastore/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.oracle.com/­database/­timesten-18.1
DeveloperAmazonGoogleApache Software FoundationOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release2007200820141998
Current release3.5.0 ( 2.13), September 202311 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
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 languageScala
Server operating systemshostedhostedLinux
OS X
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyes, details hereyesyes
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.nonono
Secondary indexesyes infoAll columns are indexed automaticallyyesnoyes
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnousing Google App EnginenoPL/SQL
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using PaxosnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowno
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 or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
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 TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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)nofine grained access rights according to SQL-standard

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More resources
Amazon SimpleDBGoogle Cloud DatastoreSpark SQLTimesTen
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