DBMS > Apache Phoenix vs. DolphinDB vs. RRDtool

System Properties Comparison Apache Phoenix vs. DolphinDB vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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.

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

phoenix.apache.org

www.dolphindb.com

oss.oetiker.ch/rrdtool

Technical documentation

phoenix.apache.org

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

oss.oetiker.ch/rrdtool/doc

Developer

Apache Software Foundation

DolphinDB, Inc

Tobias Oetiker

Initial release

2014

2018

1999

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

v2.00.4, January 2022

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community version available

Open Source

GPL V2 and FLOSS

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++

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Linux
Unix
Windows

Linux
Windows

HP-UX
Linux

Data scheme

yes

late-bound, schema-on-read capabilities

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC

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

in-process shared library
Pipes

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Administrators, Users, Groups

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More resources

DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021, Krishna Maheshwari (sponsor)

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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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2 June 2016, AWS Blog

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27 March 2017, SDTimes.com

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