DBMS > Dragonfly vs. Drizzle vs. H2 vs. Manticore Search

System Properties Comparison Dragonfly vs. Drizzle vs. H2 vs. Manticore Search

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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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

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

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

Primary database model

Key-value store

Relational DBMS

Search engine

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	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Website

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.h2database.com

manticoresearch.com

Technical documentation

www.dragonflydb.io/docs

www.h2database.com/html/main.html

manual.manticoresearch.com

Developer

DragonflyDB team and community contributors

Drizzle project, originally started by Brian Aker

Thomas Mueller

Manticore Software

Initial release

2023

2008

2005

2017

Current release

1.0, March 2023

7.2.4, September 2012

2.2.220, July 2023

6.0, February 2023

License

Commercial or Open Source

Open Source

BSL 1.1

Open Source

GNU GPL

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GPL version 2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

All OS with a Java VM

FreeBSD
Linux
macOS
Windows

Data scheme

scheme-free

yes

Fixed schema

Typing

predefined data types such as float or date

strings, hashes, lists, sets, sorted sets, bit arrays

yes

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

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

full-text index on all search fields

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC

JDBC
ODBC

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

Supported programming languages

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

C
C++
Java
PHP

Java

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

Server-side scripts

Stored procedures

Lua

Java Stored Procedures and User-Defined Functions

user defined functions

Triggers

publish/subscribe channels provide some trigger functionality

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Synchronous replication based on Galera library

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes, strict serializability by the server

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

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

In-memory capabilities

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

yes

User concepts

Access control

Password-based authentication

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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More resources

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