DBMS > Faircom DB vs. OpenMLDB vs. PouchDB vs. TempoIQ

System Properties Comparison Faircom DB vs. OpenMLDB vs. PouchDB vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It 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.

An open-source machine learning database that provides a feature platform for training and inference

JavaScript DBMS with an API inspired by CouchDB

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Document store

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

www.faircom.com/products/faircom-db

openmldb.ai

pouchdb.com

tempoiq.com (offline)

Technical documentation

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

openmldb.ai/docs/zh/main

pouchdb.com/guides

Developer

FairCom Corporation

4 Paradigm Inc.

Apache Software Foundation

TempoIQ

Initial release

1979

2020

2012

Current release

V12, November 2020

2024-2 February 2024

7.1.1, June 2019

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

ANSI C, C++

C++, Java, Scala

JavaScript

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)

Data scheme

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

Fixed schema

schema-free

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.

Secondary indexes

yes

via views

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

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

JDBC
SQLAlchemy

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API

Supported programming languages

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

C++
Go
Java
Python
Scala

JavaScript

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

View functions in JavaScript

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

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).

Source-replica replication

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

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

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

fine grained access rights according to SQL-standard

simple authentication-based access control

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More resources

DB-Engines blog posts

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