DBMS > Apache Druid vs. DolphinDB vs. EsgynDB vs. Oracle Berkeley DB vs. RRDtool

System Properties Comparison Apache Druid vs. DolphinDB vs. EsgynDB vs. Oracle Berkeley DB vs. RRDtool

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality 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.

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

Widely used in-process key-value store

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

Time Series DBMS

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Website

druid.apache.org

www.dolphindb.com

www.esgyn.cn

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

oss.oetiker.ch/rrdtool

Technical documentation

druid.apache.org/docs/latest/design

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

docs.oracle.com/cd/E17076_05/html/index.html

oss.oetiker.ch/rrdtool/doc

Developer

Apache Software Foundation and contributors

DolphinDB, Inc

Esgyn

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Tobias Oetiker

Initial release

2012

2018

2015

1994

1999

Current release

29.0.1, April 2024

v2.00.4, January 2022

18.1.40, May 2020

1.8.0, 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

free community version available

commercial

Open Source

commercial license 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++

C++, Java

C, Java, C++ (depending on the Berkeley DB edition)

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

Server operating systems

Linux
OS X
Unix

Linux
Windows

Linux

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

HP-UX
Linux

Data scheme

yes

schema-less columns are supported

yes

schema-free

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.

yes

only with the Berkeley DB XML edition

Exporting into and restoring from XML files possible

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

ADO.NET
JDBC
ODBC

in-process shared library
Pipes

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

All languages supporting JDBC/ODBC/ADO.Net

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

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

yes

Java Stored Procedures

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

Multi-source replication between multi datacenters

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Administrators, Users, Groups

fine grained access rights according to SQL-standard

More information provided by the system vendor

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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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