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DBMS > Amazon Aurora vs. GridGain vs. Hawkular Metrics vs. Hazelcast vs. Spark SQL

System Properties Comparison Amazon Aurora vs. GridGain vs. Hawkular Metrics vs. Hazelcast vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGridGain  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHazelcast  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonGridGain is an in-memory computing platform, built on Apache IgniteHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A widely adopted in-memory data gridSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMSKey-value storeRelational DBMS
Secondary database modelsDocument 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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.gridgain.comwww.hawkular.orghazelcast.comspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlwww.gridgain.com/­docs/­index.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidehazelcast.org/­imdg/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonGridGain Systems, Inc.Community supported by Red HatHazelcastApache Software Foundation
Initial release20152007201420082014
Current releaseGridGain 8.5.15.3.6, November 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0
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 languageJava, C++, .NetJavaJavaScala
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
All OS with a Java VMLinux
OS X
Windows
Data schemeyesyesschema-freeschema-freeyes
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.yesyesnoyes infothe object must implement a serialization strategyno
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLnoSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP RESTJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
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++
Java
PHP
Python
Ruby
Scala
Go
Java
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes (compute grid and cache interceptors can be used instead)noyes infoEvent Listeners, Executor Servicesno
Triggersyesyes (cache interceptors and events)yes infovia Hawkular Alertingyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infobased on CassandraShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes (replicated cache)selectable replication factor infobased on Cassandrayes infoReplicated Mapnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)noyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoone or two-phase-commit; repeatable reads; read commitedno
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.yesyesnoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsnoRole-based access controlno

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More resources
Amazon AuroraGridGainHawkular MetricsHazelcastSpark SQL
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