DBMS > DolphinDB vs. Graphite vs. Oracle Rdb vs. Sequoiadb

System Properties Comparison DolphinDB vs. Graphite vs. Oracle Rdb vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

NewSQL database with distributed OLTP and SQL

Primary database model

Time Series DBMS

Relational DBMS

Document store
Relational DBMS

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	1.08
Rank	#184	Overall
	#85	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

www.dolphindb.com

github.com/graphite-project/graphite-web

www.oracle.com/database/technologies/related/rdb.html

www.sequoiadb.com

Technical documentation

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

graphite.readthedocs.io

www.oracle.com/database/technologies/related/rdb-doc.html

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

DolphinDB, Inc

Chris Davis

Oracle, originally developed by Digital Equipment Corporation (DEC)

Sequoiadb Ltd.

Initial release

2018

2006

1984

2013

Current release

v2.00.4, January 2022

7.4.1.1, 2021

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache 2.0

commercial

Open Source

Server: AGPL; Client: Apache V2

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++

Python

C++

Server operating systems

Linux
Windows

Linux
Unix

HP Open VMS

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

yes

oid, date, timestamp, binary, regex

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

SQL-like query language

yes

SQL-like query language

APIs and other access methods

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

HTTP API
Sockets

proprietary protocol using JSON

Supported programming languages

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

JavaScript (Node.js)
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

yes, on a single node

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

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

simple password-based access control

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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