DBMS > Amazon Neptune vs. Atos Standard Common Repository vs. Blueflood vs. searchxml vs. Yaacomo

System Properties Comparison Amazon Neptune vs. Atos Standard Common Repository vs. Blueflood vs. searchxml vs. Yaacomo

Editorial information provided by DB-Engines

Name

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

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Fast, reliable graph database built for the cloud

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

Scalable TimeSeries DBMS based on Cassandra

DBMS for structured and unstructured content wrapped with an application server

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Time Series DBMS

Native XML DBMS
Search engine

Relational DBMS

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

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

aws.amazon.com/neptune

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

blueflood.io

www.searchxml.net/category/products

yaacomo.com

Technical documentation

aws.amazon.com/neptune/developer-resources

github.com/rax-maas/blueflood/wiki

www.searchxml.net/support/handouts

Developer

Amazon

Atos Convergence Creators

Rackspace

informationpartners gmbh

Q2WEB GmbH

Initial release

2017

2016

2013

2015

2009

Current release

1703

1.0

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

C++

Server operating systems

hosted

Linux

Linux
OS X

Windows

Android
Linux
Windows

Data scheme

schema-free

Schema and schema-less with LDAP views

predefined scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

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

SQL

Support of SQL

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

LDAP

HTTP REST

RESTful HTTP API
WebDAV
XQuery
XSLT

JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

All languages with LDAP bindings

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

Sharding

based on Cassandra

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

yes

selectable replication factor

based on Cassandra

yes

sychronisation to multiple collections

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

LDAP bind authentication

Domain, group and role-based access control at the document level and for application services

fine grained access rights according to SQL-standard

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