DBMS > Drizzle vs. MySQL vs. Sequoiadb vs. Splice Machine vs. TimesTen

System Properties Comparison Drizzle vs. MySQL vs. Sequoiadb vs. Splice Machine vs. TimesTen

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.

Widely used open source RDBMS

NewSQL database with distributed OLTP and SQL

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Key/Value like access via memcached API

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.mysql.com

www.sequoiadb.com

splicemachine.com

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

Technical documentation

dev.mysql.com/doc

www.sequoiadb.com/en/index.php?m=Files&a=index

splicemachine.com/how-it-works

docs.oracle.com/database/timesten-18.1

Developer

Drizzle project, originally started by Brian Aker

Oracle

since 2010, originally MySQL AB, then Sun

Sequoiadb Ltd.

Splice Machine

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2008

1995

2013

2014

1998

Current release

7.2.4, September 2012

8.4.0, April 2024

3.1, March 2021

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Server: AGPL; Client: Apache V2

Open Source

AGPL 3.0, commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

C++

C and C++

C++

Java

Server operating systems

FreeBSD
Linux
OS X

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL-like query language

yes

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC
Proprietary native API

proprietary protocol using JSON

JDBC
Native Spark Datasource
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C++
Java
PHP

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

.Net
C++
Java
PHP
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

proprietary syntax

JavaScript

yes

Java

PL/SQL

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

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

not for MyISAM storage engine

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

Users with fine-grained authorization concept

no user groups or roles

simple password-based access control

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

fine grained access rights according to SQL-standard

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