DBMS > BigchainDB vs. Dgraph vs. IRONdb vs. RRDtool vs. SQLite

System Properties Comparison BigchainDB vs. Dgraph vs. IRONdb vs. RRDtool vs. SQLite

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Distributed and scalable native Graph DBMS

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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.

Widely used embeddable, in-process RDBMS

Primary database model

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	1.48
Rank	#158	Overall
	#15	Graph DBMS

Score	2.14
Rank	#124	Overall
	#10	Time Series DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

www.bigchaindb.com

dgraph.io

www.circonus.com/solutions/time-series-database/

oss.oetiker.ch/rrdtool

www.sqlite.org

Technical documentation

bigchaindb.readthedocs.io/en/latest

dgraph.io/docs

docs.circonus.com/irondb/category/getting-started

oss.oetiker.ch/rrdtool/doc

www.sqlite.org/docs.html

Developer

Dgraph Labs, Inc.

Circonus LLC.

Tobias Oetiker

Dwayne Richard Hipp

Initial release

2016

2017

1999

2000

Current release

V0.10.20, January 2018

1.8.0, 2022

3.45.2 (12 March 2024), March 2024

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache 2.0

commercial

Open Source

GPL V2 and FLOSS

Open Source

Public Domain

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

Python

C and C++

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

Server operating systems

Linux

Linux
OS X
Windows

Linux

HP-UX
Linux

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

text, numeric, histograms

Numeric data only

yes

not rigid because of 'dynamic typing' concept.

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

SQL-92 is not fully supported

APIs and other access methods

CLI Client
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

HTTP API

in-process shared library
Pipes

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Automatic, metric affinity per node

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Synchronous replication via Raft

configurable replication factor, datacenter aware

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

via file-system locks

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

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

yes

Planned for future releases

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