DBMS > EventStoreDB vs. RRDtool vs. searchxml vs. YottaDB

System Properties Comparison EventStoreDB vs. RRDtool vs. searchxml vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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.

DBMS for structured and unstructured content wrapped with an application server

A fast and solid embedded Key-value store

Primary database model

Event Store

Time Series DBMS

Native XML DBMS
Search engine

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

www.eventstore.com

oss.oetiker.ch/rrdtool

www.searchxml.net/category/products

yottadb.com

Technical documentation

developers.eventstore.com

oss.oetiker.ch/rrdtool/doc

www.searchxml.net/support/handouts

yottadb.com/resources/documentation

Developer

Event Store Limited

Tobias Oetiker

informationpartners gmbh

YottaDB, LLC

Initial release

2012

1999

2015

2001

Current release

21.2, February 2021

1.8.0, 2022

1.0

License

Commercial or Open Source

Open Source

GPL V2 and FLOSS

commercial

Open Source

AGPL 3.0

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

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

C++

Server operating systems

Linux
Windows

HP-UX
Linux

Windows

Docker
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

Numeric data only

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.

Exporting into and restoring from XML files possible

yes

Secondary indexes

yes

SQL

Support of SQL

by using the Octo plugin

APIs and other access methods

in-process shared library
Pipes

RESTful HTTP API
WebDAV
XQuery
XSLT

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

C++

most other programming languages supported via APIs

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

on the application server

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

sychronisation to multiple collections

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

multiple readers, single writer

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

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

Domain, group and role-based access control at the document level and for application services

Users and groups based on OS-security mechanisms

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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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