DBMS > atoti vs. Dolt vs. EsgynDB vs. Lovefield vs. MySQL

System Properties Comparison atoti vs. Dolt vs. EsgynDB vs. Lovefield vs. MySQL

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A MySQL compatible DBMS with Git-like versioning of data and schema

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

Embeddable relational database for web apps written in pure JavaScript

Widely used open source RDBMS

Primary database model

Object oriented DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	0.45
Rank	#253	Overall
	#13	Object oriented DBMS

Score	0.93
Rank	#194	Overall
	#90	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Website

atoti.io

github.com/dolthub/dolt
www.dolthub.com

www.esgyn.cn

google.github.io/lovefield

www.mysql.com

Technical documentation

docs.atoti.io

docs.dolthub.com

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

dev.mysql.com/doc

Developer

ActiveViam

DoltHub Inc

Esgyn

Google

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2018

2015

2014

1995

Current release

2.1.12, February 2017

9.0.0, July 2024

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++, Java

JavaScript

C and C++

Server operating systems

Linux
macOS
Windows

Linux

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

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

SQL-like query language

via JavaScript builder pattern

yes

with proprietary extensions

APIs and other access methods

CLI Client
HTTP REST

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

All languages supporting JDBC/ODBC/ADO.Net

JavaScript

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Python

yes

currently in alpha release

Java Stored Procedures

yes

proprietary syntax

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Multi-source replication between multi datacenters

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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

yes

User concepts

Access control

Only one user is configurable, and must be specified in the config file at startup

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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