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DBMS > Amazon SimpleDB vs. Apache Impala vs. Faircom EDGE vs. Teradata Aster

System Properties Comparison Amazon SimpleDB vs. Apache Impala vs. Faircom EDGE vs. Teradata Aster

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Impala  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  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 ScioreAnalytic DBMS for HadoopFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value storeRelational DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#133  Overall
#23  Key-value stores
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.09
Rank#362  Overall
#53  Key-value stores
#155  Relational DBMS
Websiteaws.amazon.com/­simpledbimpala.apache.orgwww.faircom.com/­products/­faircom-edge
Technical documentationdocs.aws.amazon.com/­simpledbimpala.apache.org/­impala-docs.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaFairCom CorporationTeradata
Initial release2007201319792005
Current release4.1.0, June 2022V3, October 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercial infoRestricted, free version availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ANSI C, C++
Server operating systemshostedLinuxAndroid
Linux infoARM, x86
Raspbian
Windows
Linux
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)Flexible 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 datenoyesyes, ANSI Standard SQL Typesyes
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.noyesyes infoin Aster File Store
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyes infoANSI SQL queriesyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBCC
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyes info.Net, JavaScript, C/C++R packages
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryes infoSynchronous and asynchronous realtime replication based on transaction logsyes 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 methodsnoyes infoquery execution via MapReducenoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoacross SQL and NoSQLyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
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 infobased on Apache Sentry and KerberosFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.fine grained access rights according to SQL-standard

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More resources
Amazon SimpleDBApache ImpalaFaircom EDGE infoformerly c-treeEDGETeradata Aster
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