DBMS > BigObject vs. GridDB vs. MongoDB vs. PouchDB vs. SingleStore

System Properties Comparison BigObject vs. GridDB vs. MongoDB vs. PouchDB vs. SingleStore

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

JavaScript DBMS with an API inspired by CouchDB

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Document store

Relational DBMS

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

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Website

Technical documentation

docs.bigobject.io

docs.griddb.net

www.mongodb.com/docs/manual

pouchdb.com/guides

docs.singlestore.com

Developer

BigObject, Inc.

Toshiba Corporation

MongoDB, Inc

Apache Software Foundation

SingleStore Inc.

Initial release

2015

2013

2009

2012

2013

Current release

5.1, August 2022

6.0.7, June 2023

7.1.1, June 2019

8.5, January 2024

License

Commercial or Open Source

commercial

free community edition available

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.

Open Source

commercial

free developer edition 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.

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.

SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities

Implementation language

C++

JavaScript

C++, Go

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux

64 bit version required

Data scheme

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

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

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

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL92, SQL-like TQL (Toshiba Query Language)

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

but no triggers and foreign keys

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

HTTP REST

only for PouchDB Server
JavaScript API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

Supported programming languages

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

JavaScript

Bash
C
C#
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

JavaScript

View functions in JavaScript

yes

Triggers

yes

in MongoDB Atlas only

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

with a proxy-based framework, named couchdb-lounge

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

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

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

stores two copies of each physical data partition on two separate nodes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate consistency within container, eventual consistency across containers

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID at container level

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

optional, enabled by default

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Access rights for users can be defined per database

Access rights for users and roles

Fine grained access control via users, groups 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

SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» 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...
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SingleStore’s competitive advantages include: Easy and Simplified Architecture with...
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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

Driving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» 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

IEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more

Market metrics

GitHub trending repository
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Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Customers in various industries worldwide including US and International Industry...
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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...
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F ree Tier and Enterprise Edition
» more

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