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DBMS > Amazon Aurora vs. Apache Impala vs. Drizzle vs. Faircom EDGE vs. Hazelcast

System Properties Comparison Amazon Aurora vs. Apache Impala vs. Drizzle vs. Faircom EDGE vs. Hazelcast

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonHazelcast  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAnalytic DBMS for HadoopMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsA widely adopted in-memory data grid
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Relational DBMS
Key-value store
Secondary database modelsDocument storeDocument storeDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Websiteaws.amazon.com/­rds/­auroraimpala.apache.orgwww.faircom.com/­products/­faircom-edgehazelcast.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlimpala.apache.org/­impala-docs.htmldocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlhazelcast.org/­imdg/­docs
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerFairCom CorporationHazelcast
Initial release20152013200819792008
Current release4.1.0, June 20227.2.4, September 2012V3, October 20205.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoGNU GPLcommercial infoRestricted, free version availableOpen Source infoApache Version 2; commercial licenses available
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 languageC++C++ANSI C, C++Java
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Android
Linux infoARM, x86
Raspbian
Windows
All OS with a Java VM
Data schemeyesyesyesFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI Standard SQL Typesyes
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.yesnoyesyes infothe object must implement a serialization strategy
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infowith proprietary extensionsyes infoANSI SQL queriesSQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
JDBCADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
JCache
JPA
Memcached protocol
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
All languages supporting JDBC/ODBCC
C++
Java
PHP
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyesyes infouser defined functions and integration of map-reducenoyes info.Net, JavaScript, C/C++yes infoEvent Listeners, Executor Services
Triggersyesnono infohooks for callbacks inside the server can be used.yesyes infoEvents
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingFile partitioning infoCustomizable business rules for partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replication
Source-replica replication
yes infoSynchronous and asynchronous realtime replication based on transaction logsyes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Tunable Consistency
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesnoyesyes infowhen using SQLno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACIDone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoacross SQL and NoSQLyes
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.yesnoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Role-based access control

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More resources
Amazon AuroraApache ImpalaDrizzleFaircom EDGE infoformerly c-treeEDGEHazelcast
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