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DBMS > Amazon SimpleDB vs. Oracle Coherence vs. Spark SQL vs. Teradata

System Properties Comparison Amazon SimpleDB vs. Oracle Coherence vs. Spark SQL vs. Teradata

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonOracle Coherence  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  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 ScioreOracles in-memory data grid solutionSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelKey-value storeKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#133  Overall
#23  Key-value stores
Score1.97
Rank#129  Overall
#22  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websiteaws.amazon.com/­simpledbwww.oracle.com/­java/­coherencespark.apache.org/­sqlwww.teradata.com
Technical documentationdocs.aws.amazon.com/­simpledbdocs.oracle.com/­en/­middleware/­standalone/­coherencespark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperAmazonOracleApache Software FoundationTeradata
Initial release2007200720141984
Current release14.1, August 20233.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScala
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows
hosted
Linux
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nonoyes
Secondary indexesyes infoAll columns are indexed automaticallynonoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsRESTful HTTP APIJCache
JPA
RESTful HTTP API
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
.Net
C++
Java
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnononoyes infoUDFs, stored procedures, table functions in parallel
Triggersnoyes infoLive Eventsnoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, with selectable consistency levelnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationconfigurablenoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infooptionallyyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)authentification to access the cache via certificates or http basic authenticationnofine grained access rights according to SQL-standard

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More resources
Amazon SimpleDBOracle CoherenceSpark SQLTeradata
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