DBMS > Apache Drill vs. openGemini vs. Oracle NoSQL vs. PouchDB

System Properties Comparison Apache Drill vs. openGemini vs. Oracle NoSQL vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store
Relational DBMS

Time Series DBMS

Document store
Key-value store
Relational DBMS

Document store

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Website

drill.apache.org

www.opengemini.org
github.com/openGemini

www.oracle.com/database/nosql/technologies/nosql

pouchdb.com

Technical documentation

drill.apache.org/docs

docs.opengemini.org/guide

docs.oracle.com/en/database/other-databases/nosql-database/index.html

pouchdb.com/guides

Developer

Apache Software Foundation

Huawei and openGemini community

Oracle

Apache Software Foundation

Initial release

2012

2022

2011

2012

Current release

1.20.3, January 2023

1.1, July 2023

24.1, May 2024

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

JavaScript

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
Solaris SPARC/x86

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

optional

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP REST

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C++

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

C
C#
Go
Java
JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

off heap cache

yes

User concepts

Access control

Depending on the underlying data source

Administrators and common users accounts

Access rights for users and roles

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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