DBMS > atoti vs. DolphinDB vs. MySQL vs. OrientDB vs. PouchDB

System Properties Comparison atoti vs. DolphinDB vs. MySQL vs. OrientDB vs. PouchDB

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.

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Widely used open source RDBMS

Multi-model DBMS (Document, Graph, Key/Value)

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Object oriented DBMS

Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Document store
Graph DBMS
Key-value store

Document store

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

Technical documentation

docs.atoti.io

docs.dolphindb.cn/en/help200/index.html

dev.mysql.com/doc

www.orientdb.com/docs/last/index.html

pouchdb.com/guides

Developer

ActiveViam

DolphinDB, Inc

Oracle

since 2010, originally MySQL AB, then Sun

OrientDB LTD; CallidusCloud; SAP

Apache Software Foundation

Initial release

2018

1995

2010

2012

Current release

v2.00.4, January 2022

8.4.0, April 2024

3.2.29, March 2024

7.1.1, June 2019

License

Commercial or Open Source

commercial

free versions available

commercial

free community version available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache version 2

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

C and C++

Java

JavaScript

Server operating systems

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

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

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

yes

Secondary indexes

yes

via views

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language

yes

with proprietary extensions

SQL-like query language, no joins

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

ADO.NET
JDBC
ODBC
Proprietary native API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

Server-side scripts

Stored procedures

Python

yes

proprietary syntax

Java, Javascript

View functions in JavaScript

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

horizontal partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

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

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

relationship in graphs

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

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

Administrators, Users, Groups

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles; record level security configurable

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