DBMS > Apache Impala vs. DataFS vs. Kingbase vs. MonetDB

System Properties Comparison Apache Impala vs. DataFS vs. Kingbase vs. MonetDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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

A relational database management system that stores data in columns

Primary database model

Relational DBMS

Object oriented DBMS

Relational DBMS

Secondary database models

Document store

Graph DBMS

Document store
Spatial DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	0.44
Rank	#258	Overall
	#117	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

dev.mobiland.com/Overview.xsp

www.monetdb.org/Documentation

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Mobiland AG

BeiJing KINGBASE Information technologies inc.

MonetDB BV

Initial release

2013

2018

1999

2004

Current release

4.1.0, June 2022

1.1.263, October 2022

V8.0, August 2021

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Mozilla Public License 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 and Java

Server operating systems

Linux

Windows

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

Standard with numerous extensions

yes

SQL 2003 with some extensions

APIs and other access methods

JDBC
ODBC

.NET Client API
Proprietary client DLL
WinRT client

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C#
C++
VB.Net

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

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

yes, in SQL, C, R

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

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

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

none

Source-replica replication available in experimental status

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

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Windows-Profile

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

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

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

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19 December 2022, The China Project

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8 July 2022, PingWest

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MonetDB Foundation launched
31 January 2024, Centrum Wiskunde & Informatica (CWI)

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R — Part I
6 April 2018, Data Science Central

How MonetDB/X100 Exploits Modern CPU Performance
14 January 2020, Towards Data Science

Monet DB The Column-Store Pioneer
4 September 2019, Open Source For You

ServiceNow ordered a year's worth of hardware to avoid supply chain hassles
25 May 2022, The Register

provided by Google News

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