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DBMS > Amazon SimpleDB vs. Apache IoTDB vs. Brytlyt vs. Linter vs. Microsoft Azure Synapse Analytics

System Properties Comparison Amazon SimpleDB vs. Apache IoTDB vs. Brytlyt vs. Linter vs. Microsoft Azure Synapse Analytics

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonBrytlyt  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  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 ScioreAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLRDBMS for high security requirementsElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelKey-value storeTime Series DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websiteaws.amazon.com/­simpledbiotdb.apache.orgbrytlyt.iolinter.ruazure.microsoft.com/­services/­synapse-analytics
Technical documentationdocs.aws.amazon.com/­simpledbiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.brytlyt.iodocs.microsoft.com/­azure/­synapse-analytics
DeveloperAmazonApache Software FoundationBrytlytrelex.ruMicrosoft
Initial release20072018201619902016
Current release1.1.0, April 20235.0, August 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++ and CUDAC and C++C++
Server operating systemshostedAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hosted
Data schemeschema-freeyesyesyesyes
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.noyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyesyes
SQL infoSupport of SQLnoSQL-like query languageyesyesyes
APIs and other access methodsRESTful HTTP APIJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
ADO.NET
JDBC
ODBC
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C#
Java
PHP
Server-side scripts infoStored proceduresnoyesuser defined functions infoin PL/pgSQLyes infoproprietary syntax with the possibility to convert from PL/SQLTransact SQL
Triggersnoyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationhorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationnoACIDACIDACID
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.yes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyes

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More resources
Amazon SimpleDBApache IoTDBBrytlytLinterMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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