DBMS > Apache Impala vs. Postgres-XL vs. WakandaDB

System Properties Comparison Apache Impala vs. Postgres-XL vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Object oriented DBMS

Secondary database models

Document store

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	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

impala.apache.org

www.postgres-xl.org

wakanda.github.io

Technical documentation

impala.apache.org/impala-docs.html

www.postgres-xl.org/documentation

wakanda.github.io/doc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Wakanda SAS

Initial release

2013

2014

since 2012, originally named StormDB

2012

Current release

4.1.0, June 2022

10 R1, October 2018

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Mozilla public license

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, JavaScript

Server operating systems

Linux

Linux
macOS

Linux
OS X
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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

distributed, parallel query execution

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

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

Transaction concepts

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

ACID

MVCC

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

fine grained access rights according to SQL-standard

yes

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More resources

Recent citations in the news

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29 July 2021, iProgrammer

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

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30 June 2022, SiliconANGLE News

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12 March 2017, Uber

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27 October 2017, KDnuggets

provided by Google News

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