DBMS > Cubrid vs. HEAVY.AI vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. WakandaDB

System Properties Comparison Cubrid vs. HEAVY.AI vs. Lovefield vs. Microsoft Azure Synapse Analytics vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

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

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

google.github.io/lovefield

azure.microsoft.com/services/synapse-analytics

wakanda.github.io

Technical documentation

cubrid.org/manuals

docs.heavy.ai

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.microsoft.com/azure/synapse-analytics

wakanda.github.io/doc

Developer

CUBRID Corporation, CUBRID Foundation

HEAVY.AI, Inc.

Google

Microsoft

Wakanda SAS

Initial release

2008

2016

2014

2016

2012

Current release

11.0, January 2021

5.10, January 2022

2.1.12, February 2017

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

commercial

Open Source

AGPLv3, extended commercial license 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

C, C++, Java

C++ and CUDA

JavaScript

C++

C++, JavaScript

Server operating systems

Linux
Windows

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

hosted

Linux
OS X
Windows

Data scheme

yes

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

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

C#
Java
PHP

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures

Transact SQL

yes

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

none

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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