DBMS > Atos Standard Common Repository vs. etcd vs. MongoDB vs. RRDtool vs. Sphinx

System Properties Comparison Atos Standard Common Repository vs. etcd vs. MongoDB vs. RRDtool 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

A distributed reliable key-value store

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

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

Primary database model

Document store
Key-value store

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

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

etcd.io
github.com/etcd-io/etcd

www.mongodb.com

oss.oetiker.ch/rrdtool

sphinxsearch.com

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.mongodb.com/docs/manual

oss.oetiker.ch/rrdtool/doc

sphinxsearch.com/docs

Developer

Atos Convergence Creators

MongoDB, Inc

Tobias Oetiker

Sphinx Technologies Inc.

Initial release

2016

2009

1999

2001

Current release

1703

3.4, August 2019

6.0.7, June 2023

1.8.0, 2022

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

GPL V2 and FLOSS

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

Java

C++

Implementations in Java (e.g. RRD4J) and C# available

C++

Server operating systems

Linux

FreeBSD
Linux
Windows

experimental

Linux
OS X
Solaris
Windows

HP-UX
Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

yes

Typing

predefined data types such as float or date

optional

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

SQL-like query language (SphinxQL)

APIs and other access methods

LDAP

gRPC
JSON over HTTP

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

in-process shared library
Pipes

Proprietary protocol

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

JavaScript

Triggers

yes

yes, watching key changes

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

none

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

none

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic execution of specific operations

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

Durability

Support for making data persistent

yes

optional, enabled by default

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

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

LDAP bind authentication

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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