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DBMS > Amazon DocumentDB vs. Apache IoTDB vs. Kinetica vs. Quasardb

System Properties Comparison Amazon DocumentDB vs. Apache IoTDB vs. Kinetica vs. Quasardb

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonKinetica  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkFully vectorized database across both GPUs and CPUsDistributed, high-performance timeseries database
Primary database modelDocument storeTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#124  Overall
#22  Document stores
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score0.13
Rank#332  Overall
#28  Time Series DBMS
Websiteaws.amazon.com/­documentdbiotdb.apache.orgwww.kinetica.comquasar.ai
Technical documentationaws.amazon.com/­documentdb/­resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.kinetica.comdoc.quasar.ai/­master
DeveloperApache Software FoundationKineticaquasardb
Initial release2019201820122009
Current release1.1.0, April 20237.1, August 20213.14.1, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++C++
Server operating systemshostedAll OS with a Java VM (>= 1.8)LinuxBSD
Linux
OS X
Windows
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binary
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
Secondary indexesyesyesyesyes infowith tags
SQL infoSupport of SQLnoSQL-like query languageSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Native API
JDBC
ODBC
RESTful HTTP API
HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Java
Python
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoyesuser defined functionsno
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Integration with Hadoop and Sparknowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyes infoTransient mode
User concepts infoAccess controlAccess rights for users and rolesyesAccess rights for users and roles on table levelCryptographically strong user authentication and audit trail

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More resources
Amazon DocumentDBApache IoTDBKineticaQuasardb
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