DBMS > Bangdb vs. Drizzle vs. MonetDB vs. RavenDB

System Properties Comparison Bangdb vs. Drizzle vs. MonetDB vs. RavenDB

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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

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

A relational database management system that stores data in columns

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

bangdb.com

www.monetdb.org

ravendb.net

Technical documentation

docs.bangdb.com

www.monetdb.org/Documentation

ravendb.net/docs

Developer

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

MonetDB BV

Hibernating Rhinos

Initial release

2012

2008

2004

2010

Current release

BangDB 2.0, October 2021

7.2.4, September 2012

Dec2023 (11.49), December 2023

5.4, July 2022

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GNU GPL

Open Source

Mozilla Public License 2.0

Open Source

AGPL version 3, commercial license available

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, C++

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Data scheme

schema-free

yes

schema-free

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

yes

with proprietary extensions

yes

SQL 2003 with some extensions

SQL-like query language (RQL)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Python

C
C++
Java
PHP

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes, in SQL, C, R

yes

Triggers

yes, Notifications (with Streaming only)

hooks for callbacks inside the server can be used.

yes

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

Sharding

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

none

Source-replica replication available in experimental status

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

User concepts

Access control

yes (enterprise version only)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

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