DBMS > Apache Impala vs. DuckDB vs. MySQL vs. SpatiaLite

System Properties Comparison Apache Impala vs. DuckDB vs. MySQL vs. SpatiaLite

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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

Widely used open source RDBMS

Spatial extension of SQLite

Primary database model

Relational DBMS

Key/Value like access via memcached API

Spatial DBMS

Secondary database models

Document store

Document store
Spatial DBMS

Relational DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	5.61
Rank	#60	Overall
	#34	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	1.56
Rank	#142	Overall
	#3	Spatial DBMS

Website

impala.apache.org

duckdb.org

www.mysql.com

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

impala.apache.org/impala-docs.html

duckdb.org/docs

dev.mysql.com/doc

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Oracle

since 2010, originally MySQL AB, then Sun

Alessandro Furieri

Initial release

2013

2018

1995

2008

Current release

4.1.0, June 2022

1.0.0, June 2024

9.0.0, July 2024

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

C and C++

C++

Server operating systems

Linux

server-less

FreeBSD
Linux
OS X
Solaris
Windows

server-less

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

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication
Source-replica replication

none

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

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or roles

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