DBMS > Amazon DynamoDB vs. Cubrid vs. HEAVY.AI vs. JSqlDb

System Properties Comparison Amazon DynamoDB vs. Cubrid vs. HEAVY.AI vs. JSqlDb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

JavaScript Query Language Database, stores JavaScript objects and primitives

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Spatial 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	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Website

aws.amazon.com/dynamodb

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

github.com/heavyai/heavydb
www.heavy.ai

jsqldb.org (offline)

Technical documentation

docs.aws.amazon.com/dynamodb

cubrid.org/manuals

docs.heavy.ai

Developer

Amazon

CUBRID Corporation, CUBRID Foundation

HEAVY.AI, Inc.

Konrad von Backstrom

Initial release

2012

2008

2016

2018

Current release

11.0, January 2021

5.10, January 2022

0.8, December 2018

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

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

C++ and CUDA

Server operating systems

hosted

Linux
Windows

Linux

Linux
macOS
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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
Thrift
Vega

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

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures

functions in JavaScript

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication

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

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

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

using RocksDB

In-memory capabilities

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

yes

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.