DBMS > Bangdb vs. Drizzle vs. Manticore Search vs. Newts

System Properties Comparison Bangdb vs. Drizzle vs. Manticore Search vs. Newts

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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.

Multi-storage database for search, including full-text search.

Time Series DBMS based on Cassandra

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Search engine

Time Series DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

using the Manticore Columnar Library

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	0.29
Rank	#302	Overall
	#21	Search engines

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

bangdb.com

manticoresearch.com

opennms.github.io/newts

Technical documentation

docs.bangdb.com

manual.manticoresearch.com

github.com/OpenNMS/newts/wiki

Developer

Sachin Sinha, BangDB

Drizzle project, originally started by Brian Aker

Manticore Software

OpenNMS Group

Initial release

2012

2008

2017

2014

Current release

BangDB 2.0, October 2021

7.2.4, September 2012

6.0, February 2023

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GNU GPL

Open Source

GPL version 2

Open Source

Apache 2.0

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

Server operating systems

Linux

FreeBSD
Linux
OS X

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Fixed schema

schema-free

Typing

predefined data types such as float or date

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

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

full-text index on all search fields

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

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

HTTP REST
Java API

Supported programming languages

C
C#
C++
Java
Python

C
C++
Java
PHP

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java

Server-side scripts

Stored procedures

user defined functions

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

Partitioning is done manually, search queries against distributed index is supported

Sharding

based on Cassandra

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

Synchronous replication based on Galera library

selectable replication factor

based on Cassandra

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

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

The original contents of fields are not stored in the Manticore index.

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

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More resources

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