DBMS > Bangdb vs. Drizzle vs. Machbase Neo vs. Newts vs. Quasardb

System Properties Comparison Bangdb vs. Drizzle vs. Machbase Neo vs. Newts vs. Quasardb

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.

TimeSeries DBMS for AIoT and BigData

Time Series DBMS based on Cassandra

Distributed, high-performance timeseries database

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial 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	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

bangdb.com

machbase.com

opennms.github.io/newts

quasar.ai

Technical documentation

docs.bangdb.com

machbase.com/dbms

github.com/OpenNMS/newts/wiki

doc.quasar.ai/master

Developer

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

Machbase

OpenNMS Group

quasardb

Initial release

2012

2008

2013

2014

2009

Current release

BangDB 2.0, October 2021

7.2.4, September 2012

V8.0, August 2023

3.14.1, January 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GNU GPL

commercial

free test version available

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

C, C++

C++

Java

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux
macOS
Windows

Linux
OS X
Windows

BSD
Linux
OS X
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

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

with tags

SQL

Support of SQL

SQL like support with command line tool

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

HTTP REST
Java API

HTTP API

Supported programming languages

C
C#
C++
Java
Python

C
C++
Java
PHP

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Java

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

Server-side scripts

Stored procedures

Triggers

yes, Notifications (with Streaming only)

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

Sharding

based on Cassandra

Sharding

consistent hashing

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

selectable replication factor

based on Cassandra

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

Tunable consistency, set CAP knob accordingly

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

by using LevelDB

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

volatile and lookup table

yes

Transient mode

User concepts

Access control

yes (enterprise version only)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

simple password-based access control

Cryptographically strong user authentication and audit trail

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