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DBMS > EsgynDB vs. Google BigQuery vs. Lovefield vs. SQL.JS

System Properties Comparison EsgynDB vs. Google BigQuery vs. Lovefield vs. SQL.JS

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Large scale data warehouse service with append-only tables

Embeddable relational database for web apps written in pure JavaScript

Port of SQLite to JavaScript

Primary database model

Relational DBMS

Relational DBMS

Relational DBMS

Relational DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Website

cloud.google.com/bigquery

google.github.io/lovefield

Technical documentation

cloud.google.com/bigquery/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

sql.js.org/documentation/index.html

Developer

Esgyn

Google

Google

Alon Zakai

enhancements implemented by others

Initial release

2015

2010

2014

2012

Current release

2.1.12, February 2017

License

Commercial or Open Source

commercial

commercial

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

no

yes

no

no

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java

JavaScript

JavaScript

Server operating systems

Linux

hosted

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

tested with Chrome, Firefox, IE, Safari

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

Data scheme

yes

yes

yes

yes

Typing

predefined data types such as float or date

yes

yes

yes

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.

no

no

no

no

Secondary indexes

yes

no

yes

SQL

Support of SQL

yes

yes

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP/JSON API

JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

in JavaScript

no

no

Triggers

no

no

Using read-only observers

no

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

none

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

no

no

no

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

no

yes

yes

Transaction concepts

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

ACID

no

Since BigQuery is designed for querying data

ACID

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes

yes

Durability

Support for making data persistent

yes

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

no

except by serializing a db to a file

In-memory capabilities

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

no

no

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

no

no

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