DBMS > Apache Drill vs. Apache Pinot vs. Atos Standard Common Repository vs. GridDB vs. MongoDB

System Properties Comparison Apache Drill vs. Apache Pinot vs. Atos Standard Common Repository vs. GridDB vs. MongoDB

Editorial information provided by DB-Engines

Name

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

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

Scalable in-memory time series database optimized for IoT and Big Data

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

Document store
Relational DBMS

Relational DBMS

Document store
Key-value store

Time Series DBMS

Document store

Secondary database models

Key-value store
Relational 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	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Website

drill.apache.org

pinot.apache.org

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

griddb.net

www.mongodb.com

Technical documentation

drill.apache.org/docs

docs.pinot.apache.org

docs.griddb.net

www.mongodb.com/docs/manual

Developer

Apache Software Foundation

Apache Software Foundation and contributors

Atos Convergence Creators

Toshiba Corporation

MongoDB, Inc

Initial release

2012

2015

2016

2013

2009

Current release

1.20.3, January 2023

1.0.0, September 2023

1703

5.1, August 2022

6.0.7, June 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

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)

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java JDK11 or higher

Linux

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

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.

Typing

predefined data types such as float or date

yes

optional

yes

numerical, string, blob, geometry, boolean, timestamp

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 SELECT statement is SQL:2003 compliant

SQL-like query language

SQL92, SQL-like TQL (Toshiba Query Language)

Read-only SQL queries via the MongoDB Atlas SQL Interface

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

LDAP

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

C++

Go
Java
Python

All languages with LDAP bindings

C
C++
Go
Java
JavaScript (Node.js)
Perl
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

user defined functions

JavaScript

Triggers

yes

in MongoDB Atlas only

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

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.

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Immediate consistency within container, eventual consistency across containers

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

ACID at container level

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

optional, enabled by default

In-memory capabilities

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

Depending on the underlying data source

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

Depending on the underlying data source

LDAP bind authentication

Access rights for users can be defined per database

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

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

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

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

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

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

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

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

Market metrics

GitHub trending repository
» more

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

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.