DBMS > atoti vs. OrigoDB vs. Transwarp ArgoDB

System Properties Comparison atoti vs. OrigoDB vs. Transwarp ArgoDB

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Editorial information provided by DB-Engines

Name

Description

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

A fully ACID in-memory object graph database

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Object oriented DBMS

Document store
Object oriented DBMS

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	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.07
Rank	#350	Overall
	#153	Relational DBMS

Website

atoti.io

origodb.com

www.transwarp.cn/en/product/argodb

Technical documentation

docs.atoti.io

origodb.com/docs

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

Developer

ActiveViam

Robert Friberg et al

Transwarp

Initial release

2009

under the name LiveDB

License

Commercial or Open Source

commercial

free versions available

Open Source

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

Server operating systems

Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

APIs and other access methods

.NET Client API
HTTP API
LINQ

Supported programming languages

.Net

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Foreign keys

Referential integrity

depending on model

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

Write ahead log

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

Role based authorization

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