DBMS > Atos Standard Common Repository vs. HugeGraph vs. Newts vs. Rockset vs. Trafodion

System Properties Comparison Atos Standard Common Repository vs. HugeGraph vs. Newts vs. Rockset vs. Trafodion

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

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

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A fast-speed and highly-scalable Graph DBMS

Time Series DBMS based on Cassandra

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Key-value store

Secondary database models

Relational DBMS
Search engine

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

github.com/hugegraph
hugegraph.apache.org

opennms.github.io/newts

rockset.com

trafodion.apache.org

Technical documentation

hugegraph.apache.org/docs

github.com/OpenNMS/newts/wiki

docs.rockset.com

trafodion.apache.org/documentation.html

Developer

Atos Convergence Creators

Baidu

OpenNMS Group

Rockset

Apache Software Foundation, originally developed by HP

Initial release

2016

2018

2014

2019

2014

Current release

1703

0.9

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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

Linux

Linux
macOS
Unix

Linux
OS X
Windows

hosted

Linux

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

Typing

predefined data types such as float or date

optional

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

also supports composite index and range index

all fields are automatically indexed

yes

SQL

Support of SQL

Read-only SQL queries, including JOINs

yes

APIs and other access methods

LDAP

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP REST
Java API

HTTP REST

ADO.NET
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

Groovy
Java
Python

Java

Go
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

based on Cassandra

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

selectable replication factor

based on Cassandra

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

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

LDAP bind authentication

Users, roles and permissions

Access rights for users and organizations can be defined via Rockset console

fine grained access rights according to SQL-standard

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