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DBMS > Amazon DocumentDB vs. Cubrid vs. EXASOL vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. Cubrid vs. EXASOL vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonCubrid  Xexclude from comparisonEXASOL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbcubrid.com (korean)
cubrid.org (english)
www.exasol.comspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourcescubrid.org/­manualswww.exasol.com/­resourcesspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCUBRID Corporation, CUBRID FoundationExasolApache Software Foundation
Initial release2019200820002014
Current release11.0, January 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaScala
Server operating systemshostedLinux
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLnoyesyesSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
ODBC
OLE DB
.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Lua
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresuser defined functionsno
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes infoHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDno
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.noyesno
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardno

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More resources
Amazon DocumentDBCubridEXASOLSpark SQL
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