DBMS > Apache Derby vs. Dragonfly vs. QuestDB

System Properties Comparison Apache Derby vs. Dragonfly vs. QuestDB

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Editorial information provided by DB-Engines

Name

Description

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

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

A high performance open source SQL database for time series data

Primary database model

Relational DBMS

Key-value store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	3.04
Rank	#85	Overall
	#46	Relational DBMS

Score	0.53
Rank	#244	Overall
	#35	Key-value stores

Score	3.26
Rank	#79	Overall
	#6	Time Series DBMS

Website

db.apache.org/derby

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

questdb.io

Technical documentation

db.apache.org/derby/manuals/index.html

www.dragonflydb.io/docs

questdb.io/docs

Developer

Apache Software Foundation

DragonflyDB team and community contributors

QuestDB Technology Inc

Initial release

1997

2023

2014

Current release

10.17.1.0, November 2023

1.0, March 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

BSL 1.1

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

Java

C++

Java (Zero-GC), C++, Rust

Server operating systems

All OS with a Java VM

Linux

Linux
macOS
Windows

Data scheme

yes

scheme-free

yes

schema-free via InfluxDB Line Protocol

Typing

predefined data types such as float or date

yes

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL with time-series extensions

APIs and other access methods

JDBC

Proprietary protocol

RESP - REdis Serialization Protocol

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

Supported programming languages

Java

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

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

Server-side scripts

Stored procedures

Java Stored Procedures

Lua

Triggers

yes

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by timestamps)

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Source-replica replication with eventual consistency

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Atomic execution of command blocks and scripts

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

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

through memory mapped files

User concepts

Access control

fine grained access rights according to SQL-standard

Password-based authentication

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