DBMS > Atos Standard Common Repository vs. Greenplum vs. MongoDB vs. Quasardb vs. Sqrrl

System Properties Comparison Atos Standard Common Repository vs. Greenplum vs. MongoDB vs. Quasardb vs. Sqrrl

Editorial information provided by DB-Engines

Name

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

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

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

Distributed, high-performance timeseries database

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store
Spatial DBMS

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	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

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

greenplum.org

www.mongodb.com

quasar.ai

sqrrl.com

Technical documentation

docs.greenplum.org

www.mongodb.com/docs/manual

doc.quasar.ai/master

Developer

Atos Convergence Creators

Pivotal Software Inc.

MongoDB, Inc

quasardb

Amazon

originally Sqrrl Data, Inc.

Initial release

2016

2005

2009

2012

Current release

1703

7.0.0, September 2023

6.0.7, June 2023

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache 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.

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

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.

MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.
MongoDB Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.

Implementation language

Java

C++

Java

Server operating systems

Linux

Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

Linux

Data scheme

Schema and schema-less with LDAP views

yes

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.

schema-free

Typing

predefined data types such as float or date

optional

yes

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

yes

integer and binary

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

since Version 4.2

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

yes

Read-only SQL queries via the MongoDB Atlas SQL Interface

SQL-like query language

APIs and other access methods

LDAP

JDBC
ODBC

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

HTTP API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

All languages with LDAP bindings

C
Java
Perl
Python
R

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

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.

Sharding

consistent hashing

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

Source-replica replication with selectable replication factor

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

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

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

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

ACID

Multi-document ACID Transactions with snapshot isolation

ACID

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

by using LevelDB

yes

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

Transient mode

User concepts

Access control

LDAP bind authentication

fine grained access rights according to SQL-standard

Access rights for users and roles

Cryptographically strong user authentication and audit trail

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more

Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.