DBMS > Drizzle vs. Google BigQuery vs. MySQL vs. Stardog vs. WakandaDB

System Properties Comparison Drizzle vs. Google BigQuery vs. MySQL vs. Stardog 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

Widely used open source RDBMS

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

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

Key/Value like access via memcached API

Graph DBMS
RDF store

Object oriented DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

cloud.google.com/bigquery

www.mysql.com

www.stardog.com

wakanda.github.io

Technical documentation

cloud.google.com/bigquery/docs

dev.mysql.com/doc

docs.stardog.com

wakanda.github.io/doc

Developer

Drizzle project, originally started by Brian Aker

Google

Oracle

since 2010, originally MySQL AB, then Sun

Stardog-Union

Wakanda SAS

Initial release

2008

2010

1995

2010

2012

Current release

7.2.4, September 2012

8.4.0, April 2024

7.3.0, May 2020

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

C and C++

Java

C++, JavaScript

Server operating systems

FreeBSD
Linux
OS X

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

with proprietary extensions

yes

with proprietary extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

RESTful HTTP API

Supported programming languages

C
C++
Java
PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

proprietary syntax

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

hooks for callbacks inside the server can be used.

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication in HA-Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

relationships in graphs

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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)

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

yes

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