DBMS > HEAVY.AI vs. Oracle Rdb vs. Tkrzw vs. WakandaDB

System Properties Comparison HEAVY.AI vs. Oracle Rdb vs. Tkrzw vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

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

Key-value store

Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

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

www.oracle.com/database/technologies/related/rdb.html

dbmx.net/tkrzw

wakanda.github.io

Technical documentation

docs.heavy.ai

www.oracle.com/database/technologies/related/rdb-doc.html

wakanda.github.io/doc

Developer

HEAVY.AI, Inc.

Oracle, originally developed by Digital Equipment Corporation (DEC)

Mikio Hirabayashi

Wakanda SAS

Initial release

2016

1984

2020

2012

Current release

5.10, January 2022

7.4.1.1, 2021

0.9.3, August 2020

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

Open Source

Apache Version 2.0

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

C++ and CUDA

C++

C++, JavaScript

Server operating systems

Linux

HP Open VMS

Linux
macOS

Linux
OS X
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

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

APIs and other access methods

JDBC
ODBC
Thrift
Vega

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C++
Java
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

Transaction concepts

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

yes, on a single node

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

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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More resources

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