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DBMS > Amazon Aurora vs. Ehcache vs. Firebase Realtime Database vs. HEAVY.AI vs. Kinetica

System Properties Comparison Amazon Aurora vs. Ehcache vs. Firebase Realtime Database vs. HEAVY.AI vs. Kinetica

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonEhcache  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonA widely adopted Java cache with tiered storage optionsCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSKey-value storeDocument storeRelational 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
Score4.89
Rank#67  Overall
#8  Key-value stores
Score14.29
Rank#39  Overall
#6  Document stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.ehcache.orgfirebase.google.com/­products/­realtime-databasegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.ehcache.org/­documentationfirebase.google.com/­docs/­databasedocs.heavy.aidocs.kinetica.com
DeveloperAmazonTerracotta Inc, owned by Software AGGoogle infoacquired by Google 2014HEAVY.AI, Inc.Kinetica
Initial release20152009201220162012
Current release3.10.0, March 20225.10, January 20227.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
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 VMhostedLinuxLinux
Data schemeyesschema-freeschema-freeyesyes
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.yesnononono
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLyesnonoyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
JCacheAndroid
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
JavaJava
JavaScript
Objective-C
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnolimited functionality with using 'rules'nouser defined functions
Triggersyesyes infoCache Event ListenersCallbacks are triggered when data changesnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoby using Terracotta ServerSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoby using Terracotta ServerMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourceyesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardnoyes, based on authentication and database rulesfine grained access rights according to SQL-standardAccess rights for users and roles on table level

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More resources
Amazon AuroraEhcacheFirebase Realtime DatabaseHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Kinetica
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