DBMS > Atos Standard Common Repository vs. BigchainDB vs. Cassandra vs. HugeGraph vs. Newts

System Properties Comparison Atos Standard Common Repository vs. BigchainDB vs. Cassandra vs. HugeGraph vs. Newts

Editorial information provided by DB-Engines

Name

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

Description

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A fast-speed and highly-scalable Graph DBMS

Time Series DBMS based on Cassandra

Primary database model

Document store
Key-value store

Secondary database models

Vector DBMS

starting with release V5

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	103.86
Rank	#12	Overall
	#1	Wide column stores

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Website

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

www.bigchaindb.com

cassandra.apache.org

github.com/hugegraph
hugegraph.apache.org

opennms.github.io/newts

Technical documentation

bigchaindb.readthedocs.io/en/latest

cassandra.apache.org/doc/latest

hugegraph.apache.org/docs

github.com/OpenNMS/newts/wiki

Developer

Atos Convergence Creators

Apache Software Foundation

Apache top level project, originally developped by Facebook

Baidu

OpenNMS Group

Initial release

2016

2008

2018

2014

Current release

1703

4.1.3, July 2023

0.9

License

Commercial or Open Source

commercial

Open Source

AGPL v3

Open Source

Apache version 2

Open Source

Apache Version 2.0

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Python

Java

Server operating systems

Linux

BSD
Linux
OS X
Windows

Linux
macOS
Unix

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

schema-free

Typing

predefined data types such as float or date

optional

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

restricted

only equality queries, not always the best performing solution

yes

also supports composite index and range index

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

APIs and other access methods

LDAP

CLI Client
RESTful HTTP API

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP REST
Java API

Supported programming languages

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Groovy
Java
Python

Java

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

no "single point of failure"

yes

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

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Representation of geographical distribution of servers is possible

yes

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

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

Atomic execution of specific operations

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

yes

Access rights for users can be defined per object

Users, roles and permissions

More information provided by the system vendor

Specific characteristics

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Key customers

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Market metrics

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