DBMS > atoti vs. EsgynDB vs. Newts

System Properties Comparison atoti vs. EsgynDB vs. Newts

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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.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Time Series DBMS based on Cassandra

Primary database model

Object oriented DBMS

Relational DBMS

Time Series DBMS

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

Score	0.59
Rank	#242	Overall
	#10	Object oriented DBMS

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Website

atoti.io

www.esgyn.cn

opennms.github.io/newts

Technical documentation

docs.atoti.io

github.com/OpenNMS/newts/wiki

Developer

ActiveViam

Esgyn

OpenNMS Group

Initial release

2015

2014

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Apache 2.0

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++, Java

Java

Server operating systems

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP REST
Java API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java

Server-side scripts

Stored procedures

Python

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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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