DBMS > HEAVY.AI vs. STSdb vs. UniData,UniVerse vs. WakandaDB

System Properties Comparison HEAVY.AI vs. STSdb vs. UniData,UniVerse 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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

MultiValue database and application server with SQL mapping layer and meta database capabilities

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Score	3.47
Rank	#93	Overall
	#2	Multivalue DBMS

Score	0.09
Rank	#352	Overall
	#16	Object oriented DBMS

Website

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

github.com/STSSoft/STSdb4

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

wakanda.github.io

Technical documentation

docs.heavy.ai

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

wakanda.github.io/doc

Developer

HEAVY.AI, Inc.

STS Soft SC

Rocket Software

Wakanda SAS

Initial release

2016

2011

1985

2012

Current release

5.10, January 2022

4.0.8, September 2015

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

GPLv2, commercial license available

commercial

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++, JavaScript

Server operating systems

Linux

Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

optional

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

.NET Client API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C#
Java

.Net
Basic

U2 Basic
C
Java

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

U2 Basic

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

Source-replica 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

Transaction concepts

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

ACID

configurable

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights according to SQL-standard and operating system based

yes

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More resources

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