DBMS > BigchainDB vs. Graph Engine vs. Informix vs. Riak TS vs. ToroDB

System Properties Comparison BigchainDB vs. Graph Engine vs. Informix vs. Riak TS vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB 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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store

Graph DBMS
Key-value store

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Time Series DBMS

Document store

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

www.bigchaindb.com

www.graphengine.io

www.ibm.com/products/informix

github.com/torodb/server

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.graphengine.io/docs/manual

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

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

Developer

Microsoft

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Open Source, formerly Basho Technologies

8Kdata

Initial release

2016

2010

1984

2015

2016

Current release

14.10.FC5, November 2020

3.0.0, September 2022

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

MIT License

commercial

free developer edition available

Open Source

AGPL-V3

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

.NET and C

C, C++ and Java

Erlang

Java

Server operating systems

Linux

.NET

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
OS X

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

yes

string, integer, double, boolean, date, object_id

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

restricted

SQL

Support of SQL

yes

yes, limited

APIs and other access methods

CLI Client
RESTful HTTP API

RESTful HTTP API

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
F#
Visual Basic

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

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

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate 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

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Users with fine-grained authentication, authorization, and auditing controls

Access rights for users and roles

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More resources

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