DBMS > AntDB vs. Newts vs. RDF4J vs. searchxml vs. Sphinx

System Properties Comparison AntDB vs. Newts vs. RDF4J vs. searchxml vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

A scalable, multi-tenant, MPP-architectured RDBMS for OLTP and OLAP operations, highly compatible with Oracle

Time Series DBMS based on Cassandra

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

DBMS for structured and unstructured content wrapped with an application server

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

Primary database model

Relational DBMS

Time Series DBMS

RDF store

Native XML DBMS
Search engine

Search engine

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

Score	0.25
Rank	#303	Overall
	#137	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.asiainfo.com/en_us/product_aisware_antdb_detail.html

opennms.github.io/newts

rdf4j.org

www.searchxml.net/category/products

sphinxsearch.com

Technical documentation

github.com/OpenNMS/newts/wiki

rdf4j.org/documentation

www.searchxml.net/support/handouts

sphinxsearch.com/docs

Developer

AsiaInfo Technologies Limited

OpenNMS Group

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

informationpartners gmbh

Sphinx Technologies Inc.

Initial release

2014

2004

2015

2001

Current release

1.0

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

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

Java

C++

Server operating systems

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

schema-free

yes

Typing

predefined data types such as float or date

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

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL2016 compliant

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
MySQL protocol compliant
ODBC

HTTP REST
Java API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

RESTful HTTP API
WebDAV
XQuery
XSLT

Proprietary protocol

Supported programming languages

Java

Java
PHP
Python

C++

most other programming languages supported via APIs

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

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

based on Cassandra

none

yes

sychronisation to multiple collections

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

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

In-memory capabilities

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

yes

User concepts

Access control

Domain, group and role-based access control at the document level and for application services

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

AntDB: Answer to Database Evolution - Hyperconverged All-in-One Streaming Engine
22 June 2023, Bei Mo, AntDB (sponsor)

show all

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

show all

Recent citations in the news

GraphDB Goes Open Source
27 January 2020, iProgrammer

provided by Google News

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.com

Perplexity AI: From Its Use To Operation, Everything You Need To Know About Googles Newest Challenger
11 January 2024, Free Press Journal

The Pirate Bay was recently down for over a week due to a DDoS attack
29 October 2019, The Hacker News

Beyond the Concert Hall: 5 Organizations Making a Difference in Classical Music in 2018 | WQXR Editorial
22 December 2018, WQXR Radio

provided by Google News

Share this page