DBMS > Apache Druid vs. Atos Standard Common Repository vs. Datastax Enterprise vs. MongoDB

System Properties Comparison Apache Druid vs. Atos Standard Common Repository vs. Datastax Enterprise vs. MongoDB

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Editorial information provided by DB-Engines

Name

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

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

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

Primary database model

Relational DBMS
Time Series DBMS

Document store
Key-value store

Wide column store

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector 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	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	421.65
Rank	#5	Overall
	#1	Document stores

Website

druid.apache.org

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

www.datastax.com/products/datastax-enterprise

www.mongodb.com

Technical documentation

druid.apache.org/docs/latest/design

docs.datastax.com

www.mongodb.com/docs/manual

Developer

Apache Software Foundation and contributors

Atos Convergence Creators

DataStax

MongoDB, Inc

Initial release

2012

2016

2011

2009

Current release

29.0.1, April 2024

1703

6.8, April 2020

6.0.7, June 2023

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

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

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

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.

Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Linux

Linux
OS X

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-less columns are supported

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.

Typing

predefined data types such as float or date

yes

optional

yes

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

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

SQL for querying

SQL-like DML and DDL statements (CQL); Spark SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

JDBC
RESTful HTTP/JSON API

LDAP

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages with LDAP bindings

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

cell division

Sharding

no "single point of failure"

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.

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

configurable replication factor, datacenter aware, advanced replication for edge computing

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

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

Atomicity and isolation are supported for single operations

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

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

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

LDAP bind authentication

Access rights for users can be defined per object

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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Built around the flexible document data model and unified API, MongoDB is a developer...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

Annual subscription
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MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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