DBMS > Amazon DocumentDB vs. BaseX vs. Cubrid vs. Snowflake vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. BaseX vs. Cubrid vs. Snowflake vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Cloud-based data warehousing service for structured and semi-structured data

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

aws.amazon.com/documentdb

basex.org

cubrid.com (korean)
cubrid.org (english)

www.snowflake.com

sphinxsearch.com

Technical documentation

aws.amazon.com/documentdb/resources

docs.basex.org

cubrid.org/manuals

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

Developer

BaseX GmbH

CUBRID Corporation, CUBRID Foundation

Snowflake Computing Inc.

Sphinx Technologies Inc.

Initial release

2019

2007

2008

2014

2001

Current release

11.0, June 2024

11.0, January 2021

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C, C++, Java

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux
Windows

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

XQuery supports types

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

ADO.NET
JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Proprietary protocol

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Java Stored Procedures

user defined functions

Triggers

yes

via events

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

none

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-document operations

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights for users and roles

Users with fine-grained authorization concept on 4 levels

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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