DBMS > HEAVY.AI vs. Postgres-XL vs. PostgreSQL vs. WakandaDB vs. Yanza

System Properties Comparison HEAVY.AI vs. Postgres-XL vs. PostgreSQL vs. WakandaDB vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

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

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Object oriented DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	644.36
Rank	#4	Overall
	#4	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

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

www.postgres-xl.org

www.postgresql.org

wakanda.github.io

yanza.com

Technical documentation

docs.heavy.ai

www.postgres-xl.org/documentation

www.postgresql.org/docs

wakanda.github.io/doc

Developer

HEAVY.AI, Inc.

PostgreSQL Global Development Group

www.postgresql.org/developer

Wakanda SAS

Yanza

Initial release

2016

2014

since 2012, originally named StormDB

1989

1989: Postgres, 1996: PostgreSQL

2012

2015

Current release

5.10, January 2022

10 R1, October 2018

16.4, August 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

Mozilla public license

Open Source

BSD

Open Source

AGPLv3, extended commercial license available

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++ and CUDA

C++, JavaScript

Server operating systems

Linux

Linux
macOS

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux
OS X
Windows

Windows

Data scheme

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.

yes

XML type, but no XML query functionality

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

standard with numerous extensions

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

horizontal partitioning

partitioning by range, list and (since PostgreSQL 11) by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

other methods possible by using 3rd party extensions

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

ACID

MVCC

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

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
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Related products and services

3rd parties

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