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DBMS > Amazon SimpleDB vs. Apache Impala vs. Apache IoTDB vs. Google Cloud Datastore

System Properties Comparison Amazon SimpleDB vs. Apache Impala vs. Apache IoTDB vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonGoogle Cloud Datastore  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 HadoopAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelKey-value storeRelational DBMSTime Series DBMSDocument store
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
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Websiteaws.amazon.com/­simpledbimpala.apache.orgiotdb.apache.orgcloud.google.com/­datastore
Technical documentationdocs.aws.amazon.com/­simpledbimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcloud.google.com/­datastore/­docs
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationGoogle
Initial release2007201320182008
Current release4.1.0, June 20221.1.0, April 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java
Server operating systemshostedLinuxAll OS with a Java VM (>= 1.8)hosted
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenoyesyesyes, details here
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 automaticallyyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query languageSQL-like query language (GQL)
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
JDBC
Native API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesusing Google App Engine
TriggersnonoyesCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceIntegration with Hadoop and Sparkyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual ConsistencyEventual Consistency
Strong Consistency with Raft
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.
Foreign keys infoReferential integritynononoyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationnonoACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
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.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 KerberosyesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon SimpleDBApache ImpalaApache IoTDBGoogle Cloud Datastore
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