DBMS > Atos Standard Common Repository vs. BigchainDB vs. Elasticsearch vs. Newts vs. Snowflake

System Properties Comparison Atos Standard Common Repository vs. BigchainDB vs. Elasticsearch vs. Newts 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 distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Time Series DBMS based on Cassandra

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

Primary database model

Document store
Key-value store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

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

www.bigchaindb.com

www.elastic.co/elasticsearch

opennms.github.io/newts

www.snowflake.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

github.com/OpenNMS/newts/wiki

docs.snowflake.net/manuals/index.html

Developer

Atos Convergence Creators

Elastic

OpenNMS Group

Snowflake Computing Inc.

Initial release

2016

2010

2014

Current release

1703

8.6, January 2023

License

Commercial or Open Source

commercial

Open Source

AGPL v3

Open Source

Elastic License

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

Python

Java

Server operating systems

Linux

All OS with a Java VM

Linux
OS X
Windows

hosted

Data scheme

Schema and schema-less with LDAP views

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

yes

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

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

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

LDAP

CLI Client
RESTful HTTP API

Java API
RESTful HTTP/JSON API

HTTP REST
Java API

CLI Client
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Java

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

by using the 'percolation' feature

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

based on Cassandra

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

selectable replication factor

based on Cassandra

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

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

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

Memcached and Redis integration

User concepts

Access control

LDAP bind authentication

yes

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

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