DBMS > Apache Impala vs. DuckDB vs. Kingbase vs. Linter

System Properties Comparison Apache Impala vs. DuckDB vs. Kingbase vs. Linter

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

RDBMS for high security requirements

Primary database model

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

duckdb.org/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

BeiJing KINGBASE Information technologies inc.

relex.ru

Initial release

2013

2018

1999

1990

Current release

4.1.0, June 2022

0.10, February 2024

V8.0, August 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

commercial

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 Java

C and C++

Server operating systems

Linux

server-less

Linux
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

Standard with numerous extensions

yes

APIs and other access methods

JDBC
ODBC

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

All languages supporting JDBC/ODBC

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
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

yes

Source-replica replication

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

Eventual Consistency

Immediate 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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

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5 June 2024, The Register

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5 March 2024, Datanami

DuckDB: In-Process Python Analytics for Not-Quite-Big Data
31 May 2024, The New Stack

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

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