DBMS > DolphinDB vs. Drizzle vs. Firebird

System Properties Comparison DolphinDB vs. Drizzle vs. Firebird

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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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

Firebird is an open source RDBMS forked from Borland's InterBase

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	4.23
Rank	#82	Overall
	#6	Time Series DBMS

Score	21.06
Rank	#31	Overall
	#19	Relational DBMS

Website

www.dolphindb.com

www.firebirdsql.org

Technical documentation

docs.dolphindb.cn/en/help200/index.html

www.firebirdsql.org/en/reference-manuals

Developer

DolphinDB, Inc

Drizzle project, originally started by Brian Aker

Firebird Foundation

Initial release

2018

2008

2000

As fork of Borland's InterBase

Current release

v2.00.4, January 2022

7.2.4, September 2012

5.0.0, January 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

GNU GPL

Open Source

Initial Developer's Public License

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 and C++

Server operating systems

Linux
Windows

FreeBSD
Linux
OS X

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C
C++
Java
PHP

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

PSQL

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

Administrators, Users, Groups

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users with fine-grained authorization concept

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More resources

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