DBMS > Bangdb vs. Drizzle vs. EsgynDB vs. NuoDB vs. ToroDB

System Properties Comparison Bangdb vs. Drizzle vs. EsgynDB vs. NuoDB vs. ToroDB

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.

ToroDB seems to be discontinued. Therefore it 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.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

NuoDB is a webscale distributed database that supports SQL and ACID transactions

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Website

bangdb.com

www.esgyn.cn

www.3ds.com/nuodb-distributed-sql-database

github.com/torodb/server

Technical documentation

docs.bangdb.com

doc.nuodb.com

Developer

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

Esgyn

Dassault Systèmes

originally NuoDB, Inc.

8Kdata

Initial release

2012

2008

2015

2013

2016

Current release

BangDB 2.0, October 2021

7.2.4, September 2012

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GNU GPL

commercial

limited edition free

Open Source

AGPL-V3

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++

C++

C++, Java

C++

Java

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

All OS with a Java 7 VM

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

string, integer, double, boolean, date, object_id

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

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

ADO.NET
JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

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

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

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

data is dynamically stored/cached on the nodes where it is read/written

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

Multi-source replication between multi datacenters

yes

Managed transparently by NuoDB

Source-replica 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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

MVCC

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

Temporary table

User concepts

Access control

yes (enterprise version only)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

Access rights for users and roles

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