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DBMS > Amazon Aurora vs. Apache IoTDB vs. HEAVY.AI vs. Kinetica vs. Teradata Aster

System Properties Comparison Amazon Aurora vs. Apache IoTDB vs. HEAVY.AI vs. Kinetica vs. Teradata Aster

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache IoTDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAn 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 high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraiotdb.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.heavy.aidocs.kinetica.com
DeveloperAmazonApache Software FoundationHEAVY.AI, Inc.KineticaTeradata
Initial release20152018201620122005
Current release1.1.0, April 20235.10, January 20227.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2; enterprise edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ and CUDAC, C++
Server operating systemshostedAll OS with a Java VM (>= 1.8)LinuxLinuxLinux
Data schemeyesyesyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.yesnononoyes infoin Aster File Store
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLyesSQL-like query languageyesSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
Native API
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesyesnouser defined functionsR packages
Triggersyesyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoRound robinShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replicationSource-replica replicationyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
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.yesyesyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlfine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standardAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
Amazon AuroraApache IoTDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaTeradata Aster
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