DBMS > Apache Impala vs. CouchDB vs. MaxDB vs. PostGIS vs. SQLite

System Properties Comparison Apache Impala vs. CouchDB vs. MaxDB vs. PostGIS vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

A robust and reliable RDBMS optimized to run all major SAP solutions

Spatial extension of PostgreSQL

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Document store

Spatial DBMS

using the Geocouch extension

Relational DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

docs.couchdb.org/en/stable

maxdb.sap.com/documentation

postgis.net/documentation

www.sqlite.org/docs.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

SAP, acquired from Software AG (Adabas-D) in 1997

Dwayne Richard Hipp

Initial release

2013

2005

1984

2005

2000

Current release

4.1.0, June 2022

3.3.3, December 2023

7.9.10.12, February 2024

3.4.2, February 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

commercial

Limited community edition free

Open Source

GPL v2.0

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Erlang

C++

Server operating systems

Linux

Android
BSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
WebDAV

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

.Net
C#
Java
Perl
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions in JavaScript

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

yes

based on PostgreSQL

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

Source-replica replication

yes

based on PostgreSQL

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

via file-system locks

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

yes

based on PostgreSQL

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