DBMS > BigchainDB vs. Google BigQuery vs. HugeGraph vs. RethinkDB

System Properties Comparison BigchainDB vs. Google BigQuery vs. HugeGraph vs. RethinkDB

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Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

A fast-speed and highly-scalable Graph DBMS

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Website

www.bigchaindb.com

cloud.google.com/bigquery

github.com/hugegraph
hugegraph.apache.org

rethinkdb.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

cloud.google.com/bigquery/docs

hugegraph.apache.org/docs

rethinkdb.com/docs

Developer

Google

Baidu

The Linux Foundation

since July 2017

Initial release

2016

2010

2018

2009

Current release

0.9

2.4.1, August 2020

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Python

Java

C++

Server operating systems

Linux

hosted

Linux
macOS
Unix

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

APIs and other access methods

CLI Client
RESTful HTTP API

RESTful HTTP/JSON API

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Groovy
Java
Python

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

user defined functions

in JavaScript

asynchronous Gremlin script jobs

Triggers

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

depending on used storage backend, e.g. Cassandra and HBase

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users, roles and permissions

yes

users and table-level permissions

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