DBMS > Derby vs. DuckDB vs. Impala

System Properties Comparison Derby vs. DuckDB vs. Impala

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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.

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

Analytic DBMS for Hadoop

Primary database model

Relational DBMS

Secondary database models

Document store

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

Score	6.86
Rank	#61	Overall
	#35	Relational DBMS

Score	4.05
Rank	#91	Overall
	#47	Relational DBMS

Score	17.39
Rank	#37	Overall
	#23	Relational DBMS

Website

db.apache.org/derby

duckdb.org

www.cloudera.com/products/open-source/apache-hadoop/impala.html

Technical documentation

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

duckdb.org/docs

docs.cloudera.com/documentation/enterprise/latest/topics/impala.html

Developer

Apache Software Foundation

Cloudera

Initial release

1997

2018

2013

Current release

10.16.1.1, May 2022

0.9, September 2023

4.1.0, June 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

MIT License

Open Source

Apache Version 2

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++

Server operating systems

All OS with a Java VM

server-less

Linux

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC

CLI Client
JDBC

JDBC
ODBC

Supported programming languages

Java

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

All languages supporting JDBC/ODBC

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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