DBMS > Hypertable vs. Sphinx

System Properties Comparison Hypertable vs. Sphinx

Please select another system to include it in the comparison.

Our visitors often compare Hypertable and Sphinx with PostgreSQL, MySQL and MongoDB.

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Primary database model

Wide column store

Search engine

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

Score	6.95
Rank	#64	Overall
	#8	Search engines

Website

sphinxsearch.com

Technical documentation

sphinxsearch.com/docs

Developer

Hypertable Inc.

Sphinx Technologies Inc.

Initial release

2009

2001

Current release

0.9.8.11, March 2016

3.4.1, July 2021

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

Open Source

GPL version 2, commercial licence available

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

C++

Server operating systems

Linux
OS X
Windows

an inofficial Windows port is available

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

Secondary indexes

restricted

only exact value or prefix value scans

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like query language (SphinxQL)

APIs and other access methods

C++ API
Thrift

Proprietary protocol

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

User concepts

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

Non-relational SQL Market Size, Share, Trends 2022 with Comprehensive Analysis, Recent Developments, Future Estimations, Analytical Overview and Profiles of Key Players | Microsoft SQL Server, MySQL, MongoDB, PostgreSQL
25 July 2022, Digital Journal

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News

How Jennifer Lopez took control to become $400 million girl from the block
23 July 2022, The Times

provided by Google News

Share this page