DBMS > Drizzle vs. Google Cloud Bigtable vs. InterSystems IRIS vs. MySQL vs. Oracle Rdb

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. InterSystems IRIS vs. MySQL vs. Oracle Rdb

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.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

Widely used open source RDBMS

Primary database model

Relational DBMS

Key-value store
Wide column store

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	3.54
Rank	#84	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Website

cloud.google.com/bigtable

www.intersystems.com/products/intersystems-iris

www.mysql.com

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

cloud.google.com/bigtable/docs

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

dev.mysql.com/doc

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Drizzle project, originally started by Brian Aker

Google

InterSystems

Oracle

since 2010, originally MySQL AB, then Sun

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2008

2015

2018

1995

1984

Current release

7.2.4, September 2012

2023.3, June 2023

8.4.0, April 2024

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

C++

C and C++

Server operating systems

FreeBSD
Linux
OS X

hosted

AIX
Linux
macOS
Ubuntu
Windows

FreeBSD
Linux
OS X
Solaris
Windows

HP Open VMS

Data scheme

yes

schema-free

depending on used data model

yes

Flexible Schema (defined schema, partial schema, 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

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

with proprietary extensions

yes

APIs and other access methods

JDBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C++
Java
PHP

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

.Net
C++
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Internal replication in Colossus, and regional replication between two clusters in different zones

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

not for MyISAM storage engine

yes, on a single node

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 rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

yes

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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