DBMS > Atos Standard Common Repository vs. Bangdb vs. Faircom EDGE vs. Snowflake vs. Sphinx

System Properties Comparison Atos Standard Common Repository vs. Bangdb vs. Faircom EDGE vs. Snowflake vs. Sphinx

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

Converged and high performance database for device data, events, time series, document and graph

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

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

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Document store
Key-value store

Document store
Graph DBMS
Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

Search engine

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.09
Rank	#362	Overall
	#53	Key-value stores
	#155	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

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

bangdb.com

www.faircom.com/products/faircom-edge

www.snowflake.com

sphinxsearch.com

Technical documentation

docs.bangdb.com

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

Developer

Atos Convergence Creators

Sachin Sinha, BangDB

FairCom Corporation

Snowflake Computing Inc.

Sphinx Technologies Inc.

Initial release

2016

2012

1979

2014

2001

Current release

1703

BangDB 2.0, October 2021

V3, October 2020

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

Restricted, free version available

commercial

Open Source

GPL version 2, commercial licence available

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++

ANSI C, C++

C++

Server operating systems

Linux

Android
Linux

ARM, x86
Raspbian
Windows

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

Flexible Schema (defined schema, partial schema, schema free)

yes

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

yes

Typing

predefined data types such as float or date

optional

yes: string, long, double, int, geospatial, stream, events

yes, ANSI Standard SQL Types

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

secondary, composite, nested, reverse, geospatial

yes

full-text index on all search fields

SQL

Support of SQL

SQL like support with command line tool

yes

ANSI SQL queries

yes

SQL-like query language (SphinxQL)

APIs and other access methods

LDAP

Proprietary protocol
RESTful HTTP API

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

CLI Client
JDBC
ODBC

Proprietary protocol

Supported programming languages

All languages with LDAP bindings

C
C#
C++
Java
Python

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

user defined functions

Triggers

yes

yes, Notifications (with Streaming only)

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

File partitioning

Customizable business rules for partitioning

yes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor, Knob for CAP (enterprise version only)

yes

Synchronous and asynchronous realtime replication based on transaction logs

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Tunable consistency, set CAP knob accordingly

Immediate Consistency
Tunable Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

when using SQL

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

yes, optimistic concurrency control

yes

across SQL and NoSQL

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, run db with in-memory only mode

yes

User concepts

Access control

LDAP bind authentication

yes (enterprise version only)

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

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

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