DBMS > Bangdb vs. Derby vs. Drizzle

System Properties Comparison Bangdb vs. Derby vs. Drizzle

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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

Converged and high performance database for device data, events, time series, document and graph

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.15
Rank	#334	Overall
	#45	Document stores
	#31	Graph DBMS
	#31	Time Series DBMS

Score	5.30
Rank	#66	Overall
	#36	Relational DBMS

Website

bangdb.com

db.apache.org/derby

Technical documentation

docs.bangdb.com

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

Developer

Sachin Sinha, BangDB

Apache Software Foundation

Drizzle project, originally started by Brian Aker

Initial release

2012

1997

2008

Current release

BangDB 2.0, October 2021

10.17.1.0, November 2023

7.2.4, September 2012

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache version 2

Open Source

GNU GPL

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Java

C++

Server operating systems

Linux

All OS with a Java VM

FreeBSD
Linux
OS X

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

with proprietary extensions

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

Supported programming languages

C
C#
C++
Java
Python

Java

C
C++
Java
PHP

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes, Notifications (with Streaming only)

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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