DBMS > atoti vs. Sphinx vs. Trafodion vs. Transwarp ArgoDB

System Properties Comparison atoti vs. Sphinx vs. Trafodion vs. Transwarp ArgoDB

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

Transactional SQL-on-Hadoop DBMS

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Object oriented DBMS

Search engine

Relational DBMS

Secondary database models

Search engine

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.07
Rank	#350	Overall
	#153	Relational DBMS

Website

atoti.io

sphinxsearch.com

trafodion.apache.org

www.transwarp.cn/en/product/argodb

Technical documentation

docs.atoti.io

sphinxsearch.com/docs

trafodion.apache.org/documentation.html

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

ActiveViam

Sphinx Technologies Inc.

Apache Software Foundation, originally developed by HP

Transwarp

Initial release

2001

2014

Current release

3.5.1, February 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

free versions available

Open Source

GPL version 2, commercial licence available

Open Source

Apache 2.0

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

Java

C++

C++, Java

Server operating systems

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Data scheme

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.

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language (SphinxQL)

yes

APIs and other access methods

Proprietary protocol

ADO.NET
JDBC
ODBC

Supported programming languages

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Python

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

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More resources

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