DBMS > H2 vs. HEAVY.AI vs. Quasardb vs. WakandaDB

System Properties Comparison H2 vs. HEAVY.AI vs. Quasardb vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Distributed, high-performance timeseries database

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

Time Series DBMS

Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	7.57
Rank	#47	Overall
	#30	Relational DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	0.13
Rank	#332	Overall
	#28	Time Series DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

www.h2database.com

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

quasar.ai

wakanda.github.io

Technical documentation

www.h2database.com/html/main.html

docs.heavy.ai

doc.quasar.ai/master

wakanda.github.io/doc

Developer

Thomas Mueller

HEAVY.AI, Inc.

quasardb

Wakanda SAS

Initial release

2005

2016

2009

2012

Current release

2.2.220, July 2023

5.10, January 2022

3.14.1, January 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2; enterprise edition available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++ and CUDA

C++

C++, JavaScript

Server operating systems

All OS with a Java VM

Linux

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Thrift
Vega

HTTP API

RESTful HTTP API

Supported programming languages

Java

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

Sharding

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

yes

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