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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Postgres-XL vs. SQL.JS

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Postgres-XL 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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Port of SQLite to JavaScript

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	0.53
Rank	#246	Overall
	#115	Relational DBMS

Website

cloud.google.com/bigtable

www.postgres-xl.org

Technical documentation

cloud.google.com/bigtable/docs

www.postgres-xl.org/documentation

sql.js.org/documentation/index.html

Developer

Esgyn

Google

Alon Zakai

enhancements implemented by others

Initial release

2015

2015

2014

since 2012, originally named StormDB

2012

Current release

10 R1, October 2018

License

Commercial or Open Source

commercial

commercial

Open Source

Mozilla public license

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

C

JavaScript

Server operating systems

Linux

hosted

Linux
macOS

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

Data scheme

yes

schema-free

yes

yes

Typing

predefined data types such as float or date

yes

no

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

yes

XML type, but no XML query functionality

no

Secondary indexes

yes

no

yes

SQL

Support of SQL

yes

no

yes

distributed, parallel query execution

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
Go
Java
JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures

no

user defined functions

no

Triggers

no

no

yes

no

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Internal replication in Colossus, and regional replication between two clusters in different zones

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes

no

no

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

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

Atomic single-row operations

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes

yes

Durability

Support for making data persistent

yes

yes

yes

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

no

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

no

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
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