DBMS > BigchainDB vs. Dgraph vs. RRDtool vs. XTDB

System Properties Comparison BigchainDB vs. Dgraph vs. RRDtool vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

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

Distributed and scalable native Graph DBMS

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.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.bigchaindb.com

dgraph.io

oss.oetiker.ch/rrdtool

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

dgraph.io/docs

oss.oetiker.ch/rrdtool/doc

www.xtdb.com/docs

Developer

Dgraph Labs, Inc.

Tobias Oetiker

Juxt Ltd.

Initial release

2016

1999

2019

Current release

1.8.0, 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache 2.0

Open Source

GPL V2 and FLOSS

Open Source

MIT License

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

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

Clojure

Server operating systems

Linux

Linux
OS X
Windows

HP-UX
Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

CLI Client
RESTful HTTP API

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

in-process shared library
Pipes

HTTP REST
JDBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

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

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

Clojure
Java

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Synchronous replication via Raft

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

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

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

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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Recent citations in the news

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