DBMS > Apache Pinot vs. CouchDB vs. Heroic vs. OushuDB

System Properties Comparison Apache Pinot vs. CouchDB vs. Heroic vs. OushuDB

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Website

pinot.apache.org

couchdb.apache.org

github.com/spotify/heroic

www.oushu.com/product/oushuDB

Technical documentation

docs.pinot.apache.org

docs.couchdb.org/en/stable

spotify.github.io/heroic

www.oushu.com/documentation

Developer

Apache Software Foundation and contributors

Apache Software Foundation

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

Spotify

Oushu

Initial release

2015

2005

2014

Current release

1.0.0, September 2023

3.3.3, December 2023

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

Apache 2.0

commercial

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

Java

Erlang

Java

Server operating systems

All OS with a Java JDK11 or higher

Android
BSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

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

via views

yes

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

Full-featured ANSI SQL support

APIs and other access methods

JDBC

RESTful HTTP/JSON API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC

Supported programming languages

Go
Java
Python

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

C
C++

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

improved architecture with release 2.0

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

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

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 can be defined per database

Kerberos, SSL and role based access

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Recent citations in the news

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