DBMS > AgensGraph vs. Bangdb vs. IRONdb vs. Riak TS

System Properties Comparison AgensGraph vs. Bangdb vs. IRONdb vs. Riak TS

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Editorial information provided by DB-Engines

Name

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

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Converged and high performance database for device data, events, time series, document and graph

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Graph DBMS
Relational DBMS

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

bitnine.net/agensgraph

bangdb.com

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

Technical documentation

bitnine.net/documentation

docs.bangdb.com

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

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Bitnine Global Inc.

Sachin Sinha, BangDB

Circonus LLC.

Open Source, formerly Basho Technologies

Initial release

2016

2012

2017

2015

Current release

2.1, December 2018

BangDB 2.0, October 2021

V0.10.20, January 2018

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

BSD 3

commercial

Open Source

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

C, C++

C and C++

Erlang

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X

Data scheme

depending on used data model

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

yes

text, numeric, histograms

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

restricted

SQL

Support of SQL

yes

SQL like support with command line tool

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

yes, limited

APIs and other access methods

Cypher Query Language
JDBC

Proprietary protocol
RESTful HTTP API

HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

C
Java
JavaScript
Python

C
C#
C++
Java
Python

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

yes, in Lua

Erlang

Triggers

yes, Notifications (with Streaming only)

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Automatic, metric affinity per node

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor, Knob for CAP (enterprise version only)

configurable replication factor, datacenter aware

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

User concepts

Access control

fine grained access rights according to SQL-standard

yes (enterprise version only)

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