DBMS > Derby vs. EJDB vs. Prometheus vs. Quasardb

System Properties Comparison Derby vs. EJDB vs. Prometheus vs. Quasardb

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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)

Open-source Time Series DBMS and monitoring system

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Document store

Time Series DBMS

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

db.apache.org/derby

github.com/Softmotions/ejdb

prometheus.io

quasar.ai

Technical documentation

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

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

prometheus.io/docs

doc.quasar.ai/master

Developer

Apache Software Foundation

Softmotions

quasardb

Initial release

1997

2012

2015

2009

Current release

10.17.1.0, November 2023

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GPLv2

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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
Windows

BSD
Linux
OS X
Windows

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

Numeric data only

yes

integer and binary

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

Import of XML data possible

Secondary indexes

yes

with tags

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC

in-process shared library

RESTful HTTP/JSON API

HTTP API

Supported programming languages

Java

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

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

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

by Federation

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate 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

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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