DBMS > Drizzle vs. Google BigQuery vs. Infobright vs. Percona Server for MySQL vs. WakandaDB

System Properties Comparison Drizzle vs. Google BigQuery vs. Infobright vs. Percona Server for MySQL vs. WakandaDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Large scale data warehouse service with append-only tables

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

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

Object oriented DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	2.03
Rank	#122	Overall
	#57	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

cloud.google.com/bigquery

ignitetech.com/softwarelibrary/infobrightdb

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

wakanda.github.io

Technical documentation

cloud.google.com/bigquery/docs

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

wakanda.github.io/doc

Developer

Drizzle project, originally started by Brian Aker

Google

Ignite Technologies Inc.; formerly InfoBright Inc.

Percona

Wakanda SAS

Initial release

2008

2010

2005

2008

2012

Current release

7.2.4, September 2012

8.0.36-28, 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

GNU GPL

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

GPL version 2

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

C and C++

C++, JavaScript

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
Windows

Linux

Linux
OS X
Windows

Data scheme

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.

yes

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C
C++
Java
PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica 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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Users with fine-grained authorization concept

no user groups or roles

yes

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