DBMS > Faircom DB vs. Sphinx vs. TempoIQ

System Properties Comparison Faircom DB vs. Sphinx vs. TempoIQ

Please select another system to include it in the comparison.

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.

Open source search engine for searching in data from different sources, e.g. relational databases

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

Primary database model

Key-value store
Relational DBMS

Search engine

Time Series DBMS

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

Score	0.17
Rank	#319	Overall
	#47	Key-value stores
	#141	Relational DBMS

Score	5.79
Rank	#56	Overall
	#5	Search engines

Website

www.faircom.com/products/faircom-db

sphinxsearch.com

tempoiq.com (offline)

Technical documentation

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

sphinxsearch.com/docs

Developer

FairCom Corporation

Sphinx Technologies Inc.

TempoIQ

Initial release

1979

2001

2012

Current release

V13, July 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

GPL version 2, commercial licence available

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++

Server operating systems

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

easily portable to other OSs

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

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

yes

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

full-text index on all search fields

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

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

Proprietary protocol

HTTP API

Supported programming languages

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

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

Sharding

Partitioning is done manually, search queries against distributed index is supported

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).

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

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

The original contents of fields are not stored in the Sphinx index.

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

simple authentication-based access control

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

show all

Recent citations in the news

Motorola Solutions Strengthens FairCom Partnership Through FairCom Brazil Dev Day
20 February 2025, Business Wire

Trend-Setting Products in Data and Information Management for 2025
5 December 2024, Database Trends and Applications

provided by Google News

Manticore is on search for new investment and partners
9 December 2024, Blocks and Files

Brainiacs Episode 13: Sphinx Formations, Fake News, and “The Mom Penalty”
23 February 2024, NYU

Switching From Sphinx to MkDocs Documentation – What Did I Gain and Lose
2 February 2024, Towards Data Science

Manticore is a Faster Alternative to Elasticsearch in C++
25 July 2022, HackerNoon

10 Years of Building the Security Intelligence Graph: A Tech Retrospective
28 April 2020, Recorded Future

provided by Google News

Share this page