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DBMS > Amazon SimpleDB vs. Apache IoTDB vs. Hazelcast vs. IRONdb

System Properties Comparison Amazon SimpleDB vs. Apache IoTDB vs. Hazelcast vs. IRONdb

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHazelcast  Xexclude from comparisonIRONdb  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded 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 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 FlinkA widely adopted in-memory data gridA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelKey-value storeTime Series DBMSKey-value storeTime Series DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
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
Score5.97
Rank#57  Overall
#6  Key-value stores
Websiteaws.amazon.com/­simpledbiotdb.apache.orghazelcast.comwww.circonus.com/solutions/time-series-database/
Technical documentationdocs.aws.amazon.com/­simpledbiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhazelcast.org/­imdg/­docsdocs.circonus.com/irondb/category/getting-started
DeveloperAmazonApache Software FoundationHazelcastCirconus LLC.
Initial release2007201820082017
Current release1.1.0, April 20235.3.6, November 2023V0.10.20, January 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++
Server operating systemshostedAll OS with a Java VM (>= 1.8)All OS with a Java VMLinux
Data schemeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datenoyesyesyes infotext, numeric, histograms
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 infothe object must implement a serialization strategyno
Secondary indexesyes infoAll columns are indexed automaticallyyesyesno
SQL infoSupport of SQLnoSQL-like query languageSQL-like query languageSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsRESTful HTTP APIJDBC
Native API
JCache
JPA
Memcached protocol
RESTful HTTP API
HTTP API
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnoyesyes infoEvent Listeners, Executor Servicesyes, in Lua
Triggersnoyesyes infoEventsno
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)ShardingAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infoReplicated Mapconfigurable replication factor, datacenter aware
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparkyesno
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 Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate consistency per node, eventual consistency across nodes
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 applicationnoone or two-phase-commit; repeatable reads; read commitedno
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.yesyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesRole-based access controlno

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More resources
Amazon SimpleDBApache IoTDBHazelcastIRONdb
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