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DBMS > Amazon DocumentDB vs. Atos Standard Common Repository vs. Cubrid vs. Databricks vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Atos Standard Common Repository vs. Cubrid vs. Databricks vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonCubrid  Xexclude from comparisonDatabricks  Xexclude from comparisonSphinx  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeDocument store
Key-value store
Relational DBMSDocument store
Relational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#124  Overall
#22  Document stores
Score0.95
Rank#188  Overall
#86  Relational DBMS
Score86.46
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score5.92
Rank#57  Overall
#6  Search engines
Websiteaws.amazon.com/­documentdbatos.net/en/convergence-creators/portfolio/standard-common-repositorycubrid.com (korean)
cubrid.org (english)
www.databricks.comsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcescubrid.org/­manualsdocs.databricks.comsphinxsearch.com/­docs
DeveloperAtos Convergence CreatorsCUBRID Corporation, CUBRID FoundationDatabricksSphinx Technologies Inc.
Initial release20192016200820132001
Current release170311.0, January 20213.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++, JavaC++
Server operating systemshostedLinuxLinux
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeSchema and schema-less with LDAP viewsyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesoptionalyesno
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.noyesnoyes
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoyeswith Databricks SQLSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)LDAPADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
RESTful HTTP API
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
All languages with LDAP bindingsC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonoJava Stored Proceduresuser defined functions and aggregatesno
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsAtomic execution of specific operationsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users and rolesLDAP bind authenticationfine grained access rights according to SQL-standardno
More information provided by the system vendor
Amazon DocumentDBAtos Standard Common RepositoryCubridDatabricksSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon DocumentDBAtos Standard Common RepositoryCubridDatabricksSphinx
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