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DBMS > Amazon SimpleDB vs. Apache Impala vs. BaseX vs. Google Cloud Bigtable

System Properties Comparison Amazon SimpleDB vs. Apache Impala vs. BaseX vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Impala  Xexclude from comparisonBaseX  Xexclude from comparisonGoogle Cloud Bigtable  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 ScioreAnalytic DBMS for HadoopLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelKey-value storeRelational DBMSNative XML DBMSKey-value store
Wide column store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#128  Overall
#22  Key-value stores
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score1.56
Rank#141  Overall
#4  Native XML DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Websiteaws.amazon.com/­simpledbimpala.apache.orgbasex.orgcloud.google.com/­bigtable
Technical documentationdocs.aws.amazon.com/­simpledbimpala.apache.org/­impala-docs.htmldocs.basex.orgcloud.google.com/­bigtable/­docs
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaBaseX GmbHGoogle
Initial release2007201320072015
Current release4.1.0, June 202211.2, August 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoBSD licensecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedLinuxLinux
OS X
Windows
hosted
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datenoyesno infoXQuery supports typesno
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 automaticallyyesyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnono
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBCActionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesno
Triggersnonoyes infovia eventsno
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factornoneInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationnomultiple readers, single writerAtomic single-row operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nono
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 KerberosUsers with fine-grained authorization concept on 4 levelsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon SimpleDBApache ImpalaBaseXGoogle Cloud Bigtable
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