DBMS > EsgynDB vs. EXASOL vs. Lovefield vs. TDSQL for MySQL

System Properties Comparison EsgynDB vs. EXASOL vs. Lovefield vs. TDSQL for MySQL

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Editorial information provided by DB-Engines

Name

Description

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Embeddable relational database for web apps written in pure JavaScript

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

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	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	0.96
Rank	#192	Overall
	#88	Relational DBMS

Website

www.esgyn.cn

www.exasol.com

google.github.io/lovefield

www.tencentcloud.com/products/dcdb

Technical documentation

www.exasol.com/resources

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

www.tencentcloud.com/document/product/1042

Developer

Esgyn

Exasol

Google

Tencent

Initial release

2015

2000

2014

2013

Current release

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

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++, Java

JavaScript

Server operating systems

Linux

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

tested with Chrome, Firefox, IE, Safari

hosted

Data scheme

yes

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

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
Lua
Python
R

JavaScript

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

yes

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

Users with fine-grained authorization concept

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