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DBMS > Amazon SimpleDB vs. EsgynDB vs. MarkLogic vs. Spark SQL vs. Teradata Aster

System Properties Comparison Amazon SimpleDB vs. EsgynDB vs. MarkLogic vs. Spark SQL vs. Teradata Aster

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonMarkLogic  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionOperational and transactional Enterprise NoSQL databaseSpark SQL is a component on top of 'Spark Core' for structured data processingPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value storeRelational DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#133  Overall
#23  Key-value stores
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­simpledbwww.esgyn.cnwww.marklogic.comspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­simpledbdocs.marklogic.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonEsgynMarkLogic Corp.Apache Software FoundationTeradata
Initial release20072015200120142005
Current release11.0, December 20223.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++Scala
Server operating systemshostedLinuxLinux
OS X
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeyesschema-free infoSchema can be enforcedyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or datenoyesyesyesyes
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.noyesnoyes infoin Aster File Store
Secondary indexesyes infoAll columns are indexed automaticallyyesyesnoyes
SQL infoSupport of SQLnoyesyes infoSQL92SQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoJava Stored Proceduresyes infovia XQuery or JavaScriptnoR packages
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingShardingyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersyesnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDACID infocan act as a resource manager in an XA/JTA transactionnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, with Range Indexesnono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardRole-based access control at the document and subdocument levelsnofine grained access rights according to SQL-standard

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More resources
Amazon SimpleDBEsgynDBMarkLogicSpark SQLTeradata Aster
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