DBMS > BigObject vs. Google BigQuery vs. Percona Server for MongoDB vs. PouchDB

System Properties Comparison BigObject vs. Google BigQuery vs. Percona Server for MongoDB vs. PouchDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Large scale data warehouse service with append-only tables

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	0.50
Rank	#250	Overall
	#39	Document stores

Score	2.18
Rank	#114	Overall
	#21	Document stores

Website

bigobject.io

cloud.google.com/bigquery

www.percona.com/mongodb/software/percona-server-for-mongodb

pouchdb.com

Technical documentation

docs.bigobject.io

cloud.google.com/bigquery/docs

docs.percona.com/percona-distribution-for-mongodb

pouchdb.com/guides

Developer

BigObject, Inc.

Google

Percona

Apache Software Foundation

Initial release

2015

2010

2015

2012

Current release

3.4.10-2.10, November 2017

7.1.1, June 2019

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

GPL Version 2

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

JavaScript

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

Linux

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

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

proprietary protocol using JSON

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

JavaScript

Server-side scripts

Stored procedures

Lua

user defined functions

in JavaScript

JavaScript

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

via In-Memory Engine

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles

More information provided by the system vendor

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.