DBMS > Drizzle vs. Sequoiadb vs. Splice Machine vs. SQL.JS

System Properties Comparison Drizzle vs. Sequoiadb vs. Splice Machine vs. SQL.JS

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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.

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

Port of SQLite to JavaScript

Primary database model

Relational DBMS

Document store
Relational DBMS

Relational DBMS

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

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Website

www.sequoiadb.com

splicemachine.com

sql.js.org

Technical documentation

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

splicemachine.com/how-it-works

sql.js.org/documentation/index.html

Developer

Drizzle project, originally started by Brian Aker

Sequoiadb Ltd.

Splice Machine

Alon Zakai

enhancements implemented by others

Initial release

2008

2013

2014

2012

Current release

7.2.4, September 2012

3.1, March 2021

License

Commercial or Open Source

Open Source

GNU GPL

Open Source

Server: AGPL; Client: Apache V2

Open Source

AGPL 3.0, commercial license available

Open Source

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.

Implementation language

C++

Java

JavaScript

Server operating systems

FreeBSD
Linux
OS X

Linux

Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC

proprietary protocol using JSON

JDBC
Native Spark Datasource
ODBC

JavaScript API

Supported programming languages

C
C++
Java
PHP

.Net
C++
Java
PHP
Python

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

JavaScript

Server-side scripts

Stored procedures

JavaScript

yes

Java

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

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

Eventual Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

except by serializing a db to a file

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

simple password-based access control

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

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More resources

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