DBMS > Atos Standard Common Repository vs. BigchainDB vs. JanusGraph vs. NCache vs. Snowflake

System Properties Comparison Atos Standard Common Repository vs. BigchainDB vs. JanusGraph vs. NCache vs. Snowflake

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Open-Source and Enterprise in-memory Key-Value Store

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Key-value store

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

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

www.bigchaindb.com

janusgraph.org

www.alachisoft.com/ncache

www.snowflake.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.janusgraph.org

www.alachisoft.com/resources/docs

docs.snowflake.net/manuals/index.html

Developer

Atos Convergence Creators

Linux Foundation; originally developed as Titan by Aurelius

Alachisoft

Snowflake Computing Inc.

Initial release

2016

2017

2005

2014

Current release

1703

0.6.3, February 2023

5.3.3, April 2024

License

Commercial or Open Source

commercial

Open Source

AGPL v3

Open Source

Apache 2.0

Open Source

Enterprise Edition available

commercial

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

Python

Java

C#, .NET, .NET Core, Java

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux
Windows

hosted

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

optional

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

SQL

Support of SQL

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

APIs and other access methods

LDAP

CLI Client
RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

IDistributedCache
JCache
LINQ
Proprietary native API

CLI Client
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

Clojure
Java
Python

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

support for stored procedures with SQL-Server CLR

user defined functions

Triggers

yes

Notifications

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

yes, with selectable consistency level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

User authentification and security via Rexster Graph Server

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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