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DBMS > Amazon DocumentDB vs. Amazon SimpleDB vs. Apache IoTDB vs. BigchainDB vs. Rockset

System Properties Comparison Amazon DocumentDB vs. Amazon SimpleDB vs. Apache IoTDB vs. BigchainDB vs. Rockset

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAmazon SimpleDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonBigchainDB  Xexclude from comparisonRockset  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHosted 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 FlinkBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsA scalable, reliable search and analytics service in the cloud, built on RocksDB
Primary database modelDocument storeKey-value storeTime Series DBMSDocument storeDocument store
Secondary database modelsRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.85
Rank#138  Overall
#24  Key-value stores
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.79
Rank#212  Overall
#36  Document stores
Score0.79
Rank#211  Overall
#35  Document stores
Websiteaws.amazon.com/­documentdbaws.amazon.com/­simpledbiotdb.apache.orgwww.bigchaindb.comrockset.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.aws.amazon.com/­simpledbiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlbigchaindb.readthedocs.io/­en/­latestdocs.rockset.com
DeveloperAmazonApache Software FoundationRockset
Initial release20192007201820162019
Current release1.1.0, April 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0Open Source infoAGPL v3commercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaPythonC++
Server operating systemshostedhostedAll OS with a Java VM (>= 1.8)Linuxhosted
Data schemeschema-freeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesnodynamic typing
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.nononono infoingestion from XML files supported
Secondary indexesyesyes infoAll columns are indexed automaticallyyesall fields are automatically indexed
SQL infoSupport of SQLnonoSQL-like query languagenoRead-only SQL queries, including JOINs
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)RESTful HTTP APIJDBC
Native API
CLI Client
RESTful HTTP API
HTTP REST
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
Go
Haskell
Java
JavaScript
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyesno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnonenone infoSharding must be implemented in the applicationhorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency
Strong Consistency with Raft
Eventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsno infoConcurrent data updates can be detected by the applicationnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes,with MongoDB ord RethinkDByes
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 rolesAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)yesyesAccess rights for users and organizations can be defined via Rockset console

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More resources
Amazon DocumentDBAmazon SimpleDBApache IoTDBBigchainDBRockset
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