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DBMS > Amazon SimpleDB vs. Apache Impala vs. Apache IoTDB vs. Firebird

System Properties Comparison Amazon SimpleDB vs. Apache Impala vs. Apache IoTDB vs. Firebird

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonFirebird  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 FlinkFirebird is an open source RDBMS forked from Borland's InterBase
Primary database modelKey-value storeRelational DBMSTime Series DBMSRelational 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
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score20.50
Rank#30  Overall
#18  Relational DBMS
Websiteaws.amazon.com/­simpledbimpala.apache.orgiotdb.apache.orgwww.firebirdsql.org
Technical documentationdocs.aws.amazon.com/­simpledbimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.firebirdsql.org/­en/­reference-manuals
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationFirebird Foundation
Initial release2007201320182000 infoAs fork of Borland's InterBase
Current release4.1.0, June 20221.1.0, April 20235.0.0, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoInitial Developer's Public License
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC and C++
Server operating systemshostedLinuxAll OS with a Java VM (>= 1.8)AIX
FreeBSD
HP-UX
Linux
OS X
server-less infoFirebird Embedded Server
Solaris
Unix
Windows
Data schemeschema-freeyesyesyes
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.nono
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like query languageyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
JDBC
Native API
ADO.NET
C/C++ API
JDBC infoJaybird
ODBC
OLE DB
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Delphi
Java
JavaScript infoNode.js
Lua
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesPSQL
Triggersnonoyesyes
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)none
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 replicasSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceIntegration with Hadoop and Sparkno
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
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 applicationnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoFeatures a multi-generational MVCC architecture, readers do not block writers
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.noyes
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 KerberosyesUsers with fine-grained authorization concept

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More resources
Amazon SimpleDBApache ImpalaApache IoTDBFirebird
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