DBMS > AlaSQL vs. Google BigQuery vs. LevelDB vs. PouchDB

System Properties Comparison AlaSQL vs. Google BigQuery vs. LevelDB vs. PouchDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Large scale data warehouse service with append-only tables

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store

Document store

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

Score	0.49
Rank	#259	Overall
	#40	Document stores
	#120	Relational DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	2.75
Rank	#107	Overall
	#19	Key-value stores

Score	2.35
Rank	#116	Overall
	#22	Document stores

Website

alasql.org

cloud.google.com/bigquery

github.com/google/leveldb

pouchdb.com

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigquery/docs

github.com/google/leveldb/blob/main/doc/index.md

pouchdb.com/guides

Developer

Andrey Gershun & Mathias R. Wulff

Google

Apache Software Foundation

Initial release

2014

2010

2011

2012

Current release

1.23, February 2021

7.1.1, June 2019

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

BSD

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

JavaScript

C++

JavaScript

Server operating systems

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

hosted

Illumos
Linux
OS X
Windows

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

Data scheme

schema-free

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

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

APIs and other access methods

JavaScript API

RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

JavaScript

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

JavaScript

Server-side scripts

Stored procedures

user defined functions

in 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

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

with automatic compression on writes

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

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

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.