DBMS > Amazon DynamoDB vs. Brytlyt vs. Cubrid vs. JaguarDB vs. Newts

System Properties Comparison Amazon DynamoDB vs. Brytlyt vs. Cubrid vs. JaguarDB vs. Newts

Editorial information provided by DB-Engines

Name

Description

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

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

Performant, highly scalable DBMS for AI and IoT applications

Time Series DBMS based on Cassandra

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store
Vector DBMS

Time Series DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/dynamodb

brytlyt.io

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

www.jaguardb.com

opennms.github.io/newts

Technical documentation

docs.aws.amazon.com/dynamodb

docs.brytlyt.io

cubrid.org/manuals

www.jaguardb.com/support.html

github.com/OpenNMS/newts/wiki

Developer

Amazon

Brytlyt

CUBRID Corporation, CUBRID Foundation

DataJaguar, Inc.

OpenNMS Group

Initial release

2012

2016

2008

2015

2014

Current release

5.0, August 2023

11.0, January 2021

3.3 July 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2.0

Open Source

GPL V3.0

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++ and CUDA

C, C++, Java

C++

the server part. Clients available in other languages

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux
Windows

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC

HTTP REST
Java API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

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

Java

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Java Stored Procedures

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication

selectable replication factor

based on Cassandra

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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.

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

rights management via user accounts

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