DBMS > Drizzle vs. Google Cloud Spanner vs. Oracle Coherence vs. Sadas Engine

System Properties Comparison Drizzle vs. Google Cloud Spanner vs. Oracle Coherence vs. Sadas Engine

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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.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Oracles in-memory data grid solution

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

cloud.google.com/spanner

www.oracle.com/java/coherence

www.sadasengine.com

Technical documentation

cloud.google.com/spanner/docs

docs.oracle.com/en/middleware/standalone/coherence

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Drizzle project, originally started by Brian Aker

Google

Oracle

SADAS s.r.l.

Initial release

2008

2017

2007

2006

Current release

7.2.4, September 2012

14.1, August 2023

8.0

License

Commercial or Open Source

Open Source

GNU GPL

commercial

free trial version 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++

Java

C++

Server operating systems

FreeBSD
Linux
OS X

hosted

All OS with a Java VM

AIX
Linux
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

JDBC

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JCache
JPA
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

Supported programming languages

C
C++
Java
PHP

Go
Java
JavaScript (Node.js)
Python

.Net
C++
Java

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Triggers

hooks for callbacks inside the server can be used.

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication with 3 replicas for regional instances.

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

managed by 'Learn by Usage'

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)

authentification to access the cache via certificates or http basic authentication

Access rights for users, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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