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DBMS > Amazon Aurora vs. Databricks vs. HEAVY.AI vs. Riak KV

System Properties Comparison Amazon Aurora vs. Databricks vs. HEAVY.AI vs. Riak KV

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDatabricks  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareDistributed, fault tolerant key-value store
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score4.01
Rank#79  Overall
#9  Key-value stores
Websiteaws.amazon.com/­rds/­aurorawww.databricks.comgithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.databricks.comdocs.heavy.aiwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperAmazonDatabricksHEAVY.AI, Inc.OpenSource, formerly Basho Technologies
Initial release2015201320162009
Current release5.10, January 20223.2.0, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAErlang
Server operating systemshostedhostedLinuxLinux
OS X
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.yesyesnono
Secondary indexesyesyesnorestricted
SQL infoSupport of SQLyeswith Databricks SQLyesno
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
HTTP API
Native Erlang Interface
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Python
R
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesnoErlang
Triggersyesnoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoRound robinSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesMulti-source replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
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.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyes, using Riak Security
More information provided by the system vendor
Amazon AuroraDatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Riak KV
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon AuroraDatabricksHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Riak KV
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