DBMS > Amazon DynamoDB vs. Cubrid vs. Machbase Neo vs. Prometheus

System Properties Comparison Amazon DynamoDB vs. Cubrid vs. Machbase Neo vs. Prometheus

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

TimeSeries DBMS for AIoT and BigData

Open-source Time Series DBMS and monitoring system

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

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

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	0.07
Rank	#348	Overall
	#34	Time Series DBMS

Score	7.56
Rank	#49	Overall
	#3	Time Series DBMS

Website

aws.amazon.com/dynamodb

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

machbase.com

prometheus.io

Technical documentation

docs.aws.amazon.com/dynamodb

cubrid.org/manuals

machbase.com/dbms

prometheus.io/docs

Developer

Amazon

CUBRID Corporation, CUBRID Foundation

Machbase

Initial release

2012

2008

2013

2015

Current release

11.0, January 2021

V8.0, August 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

commercial

free test version available

Open Source

Apache 2.0

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

C, C++, Java

Server operating systems

hosted

Linux
Windows

Linux
macOS
Windows

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

RESTful HTTP/JSON API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

yes

by Federation

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

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

volatile and lookup table

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

simple password-based access control

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