DBMS > Derby vs. EJDB vs. Netezza vs. Sequoiadb

System Properties Comparison Derby vs. EJDB vs. Netezza vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Data warehouse and analytics appliance part of IBM PureSystems

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Document store

Relational DBMS

Document store
Relational DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

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

Website

db.apache.org/derby

github.com/Softmotions/ejdb

www.ibm.com/products/netezza

www.sequoiadb.com

Technical documentation

db.apache.org/derby/manuals/index.html

github.com/Softmotions/ejdb/blob/master/README.md

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

Developer

Apache Software Foundation

Softmotions

IBM

Sequoiadb Ltd.

Initial release

1997

2012

2000

2013

Current release

10.17.1.0, November 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GPLv2

commercial

Open Source

Server: AGPL; Client: Apache V2

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

Java

C++

Server operating systems

All OS with a Java VM

server-less

Linux

included in appliance

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

oid, date, timestamp, binary, regex

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

SQL-like query language

APIs and other access methods

JDBC

in-process shared library

JDBC
ODBC
OLE DB

proprietary protocol using JSON

Supported programming languages

Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

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

Eventual Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

simple password-based access control

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