DBMS > DuckDB vs. Oracle Berkeley DB vs. QuestDB

System Properties Comparison DuckDB vs. Oracle Berkeley DB vs. QuestDB

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Editorial information provided by DB-Engines

Name

Description

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Widely used in-process key-value store

A high performance open source SQL database for time series data

Primary database model

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	7.44
Rank	#44	Overall
	#27	Relational DBMS

Score	1.72
Rank	#131	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	3.26
Rank	#79	Overall
	#6	Time Series DBMS

Website

duckdb.org

www.oracle.com/database/technologies/related/berkeleydb.html

questdb.io

Technical documentation

duckdb.org/docs

docs.oracle.com/cd/E17076_05/html/index.html

questdb.io/docs

Developer

Oracle

originally developed by Sleepycat, which was acquired by Oracle

QuestDB Technology Inc

Initial release

2018

1994

2014

Current release

1.0.0, June 2024

18.1.40, May 2020

License

Commercial or Open Source

Open Source

MIT License

Open Source

commercial license available

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, Java, C++ (depending on the Berkeley DB edition)

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

Server operating systems

server-less

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free via InfluxDB Line Protocol

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

SQL with time-series extensions

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

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

Supported programming languages

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

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

over HTTP

Server-side scripts

Stored procedures

Triggers

yes

only for the SQL API

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

none

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

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID for single-table writes

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

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