DBMS > EDB Postgres vs. Google BigQuery vs. Percona Server for MySQL vs. SWC-DB vs. Yanza

System Properties Comparison EDB Postgres vs. Google BigQuery vs. Percona Server for MySQL vs. SWC-DB vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Large scale data warehouse service with append-only tables

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

A high performance, scalable Wide Column DBMS

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Wide column store

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

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

Score	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.enterprisedb.com

cloud.google.com/bigquery

www.percona.com/software/mysql-database/percona-server

github.com/kashirin-alex/swc-db
www.swcdb.org

yanza.com

Technical documentation

www.enterprisedb.com/docs

cloud.google.com/bigquery/docs

www.percona.com/downloads/Percona-Server-LATEST

Developer

EnterpriseDB

Google

Percona

Alex Kashirin

Yanza

Initial release

2005

2010

2008

2020

2015

Current release

14, December 2021

8.0.36-28, 2024

0.5, April 2021

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

commercial

Open Source

GPL version 2

Open Source

GPL V3

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C and C++

C++

Server operating systems

Linux
Windows

hosted

Linux

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

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

yes

SQL-like query language

APIs and other access methods

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

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Proprietary protocol
Thrift

HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++

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.

user defined functions

in JavaScript

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

by hash, list or range

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication
XtraDB Cluster

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users with fine-grained authorization concept

no user groups or roles

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