DBMS > Apache Pinot vs. OushuDB vs. WakandaDB

System Properties Comparison Apache Pinot vs. OushuDB vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

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

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

Score	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

pinot.apache.org

www.oushu.com/product/oushuDB

wakanda.github.io

Technical documentation

docs.pinot.apache.org

www.oushu.com/documentation

wakanda.github.io/doc

Developer

Apache Software Foundation and contributors

Oushu

Wakanda SAS

Initial release

2015

2012

Current release

1.0.0, September 2023

4.0.1, August 2020

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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

Java

C++, JavaScript

Server operating systems

All OS with a Java JDK11 or higher

Linux

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

Full-featured ANSI SQL support

APIs and other access methods

JDBC

JDBC
ODBC

RESTful HTTP API

Supported programming languages

Go
Java
Python

C
C++

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Kerberos, SSL and role based access

yes

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