DBMS > DolphinDB vs. Drizzle vs. Graph Engine vs. PouchDB vs. Trafodion

System Properties Comparison DolphinDB vs. Drizzle vs. Graph Engine vs. PouchDB vs. Trafodion

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

JavaScript DBMS with an API inspired by CouchDB

Transactional SQL-on-Hadoop DBMS

Primary database model

Time Series DBMS

Relational DBMS

Graph DBMS
Key-value store

Document store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

Technical documentation

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

www.graphengine.io/docs/manual

pouchdb.com/guides

trafodion.apache.org/documentation.html

Developer

DolphinDB, Inc

Drizzle project, originally started by Brian Aker

Microsoft

Apache Software Foundation

Apache Software Foundation, originally developed by HP

Initial release

2018

2008

2010

2012

2014

Current release

v2.00.4, January 2022

7.2.4, September 2012

7.1.1, June 2019

2.3.0, February 2019

License

Commercial or Open Source

commercial

free community version available

Open Source

GNU GPL

Open Source

MIT License

Open Source

Apache 2.0

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

C++

.NET and C

JavaScript

C++, Java

Server operating systems

Linux
Windows

FreeBSD
Linux
OS X

.NET

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

Linux

Data scheme

yes

schema-free

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

via views

yes

SQL

Support of SQL

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

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

JDBC

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET
JDBC
ODBC

Supported programming languages

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

C
C++
Java
PHP

C#
C++
F#
Visual Basic

JavaScript

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Java Stored Procedures

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

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

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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More resources

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