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DBMS > Amazon Aurora vs. GBase vs. Hazelcast vs. OpenMLDB vs. Spark SQL

System Properties Comparison Amazon Aurora vs. GBase vs. Hazelcast vs. OpenMLDB vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonGBase  Xexclude from comparisonHazelcast  Xexclude from comparisonOpenMLDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.A widely adopted in-memory data gridAn open-source machine learning database that provides a feature platform for training and inferenceSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSKey-value storeTime Series DBMSRelational DBMS
Secondary database modelsDocument storeDocument store infoJSON support with IMDG 3.12Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.02
Rank#367  Overall
#37  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorawww.gbase.cnhazelcast.comopenmldb.aispark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlhazelcast.org/­imdg/­docsopenmldb.ai/­docs/­zh/­mainspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonGeneral Data Technology Co., Ltd.Hazelcast4 Paradigm Inc.Apache Software Foundation
Initial release20152004200820202014
Current releaseGBase 8a, GBase 8s, GBase 8c5.3.6, November 20232024-2 February 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availableOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, PythonJavaC++, Java, ScalaScala
Server operating systemshostedLinuxAll OS with a Java VMLinuxLinux
OS X
Windows
Data schemeyesyesschema-freeFixed schemayes
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.yesyesyes infothe object must implement a serialization strategynono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyesStandard with numerous extensionsSQL-like query languageyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
C API
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
SQLAlchemy
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#.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Go
Java
Python
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsyes infoEvent Listeners, Executor Servicesnono
Triggersyesyesyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning (by range, list and hash) and vertical partitioningShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesyes infoReplicated MapSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitednono
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.yesyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardyesRole-based access controlfine grained access rights according to SQL-standardno

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More resources
Amazon AuroraGBaseHazelcastOpenMLDBSpark SQL
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