DBMS > Postgres-XL vs. PostgreSQL vs. Vertica vs. WakandaDB vs. Yanza

System Properties Comparison Postgres-XL vs. PostgreSQL vs. Vertica 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

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

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.

Relational DBMS

Column oriented

Object oriented DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Spatial DBMS
Time Series DBMS

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

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	644.36
Rank	#4	Overall
	#4	Relational DBMS

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

yanza.com

Technical documentation

www.postgres-xl.org/documentation

www.postgresql.org/docs

vertica.com/documentation

wakanda.github.io/doc

Developer

PostgreSQL Global Development Group

www.postgresql.org/developer

OpenText

previously Micro Focus and Hewlett Packard

Wakanda SAS

Yanza

Initial release

2014

since 2012, originally named StormDB

1989

1989: Postgres, 1996: PostgreSQL

2005

2012

2015

Current release

10 R1, October 2018

16.4, August 2024

12.0.3, January 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Mozilla public license

Open Source

BSD

commercial

Limited community edition free

Open Source

AGPLv3, extended commercial license available

commercial

free version available

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, JavaScript

Server operating systems

Linux
macOS

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

Linux

Linux
OS X
Windows

Windows

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

distributed, parallel query execution

yes

standard with numerous extensions

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

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

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

RESTful HTTP API

HTTP API

Supported programming languages

.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

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

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, PostgreSQL PL/pgSQL, with minor differences

yes

Triggers

yes

yes, called Custom Alerts

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

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

horizontal partitioning, hierarchical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark 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

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.

User concepts

Access control

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

yes

More information provided by the system vendor

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