DBMS > Faircom DB vs. OushuDB vs. PouchDB vs. RocksDB vs. Teradata Aster

System Properties Comparison Faircom DB vs. OushuDB vs. PouchDB vs. RocksDB vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

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

JavaScript DBMS with an API inspired by CouchDB

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Platform for big data analytics on multistructured data sources and types

Primary database model

Key-value store
Relational DBMS

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

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.faircom.com/products/faircom-db

www.oushu.com/product/oushuDB

pouchdb.com

rocksdb.org

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

www.oushu.com/documentation

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

Developer

FairCom Corporation

Oushu

Apache Software Foundation

Facebook, Inc.

Teradata

Initial release

1979

2012

2013

2005

Current release

V12, November 2020

4.0.1, August 2020

7.1.1, June 2019

9.2.1, May 2024

License

Commercial or Open Source

commercial

Restricted, free version available

commercial

Open Source

BSD

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

ANSI C, C++

JavaScript

C++

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux

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

Linux

Data scheme

schema free, schema optional, schema required, partial schema,

yes

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

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

in Aster File Store

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

Full-featured ANSI SQL support

yes

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

C
C++

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

View functions in JavaScript

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

yes

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

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

yes

User concepts

Access control

Fine grained access rights according to SQL-standard with additional protections for files

Kerberos, SSL and role based access

fine grained access rights according to SQL-standard

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