DBMS > BigchainDB vs. Blazegraph vs. Google BigQuery vs. Google Cloud Bigtable vs. Rockset

System Properties Comparison BigchainDB vs. Blazegraph vs. Google BigQuery vs. Google Cloud Bigtable vs. Rockset

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

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

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Large scale data warehouse service with append-only tables

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Document store

Graph DBMS
RDF store

Relational DBMS

Key-value store
Wide column store

Document store

Secondary database models

Relational DBMS
Search engine

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

www.bigchaindb.com

blazegraph.com

cloud.google.com/bigquery

cloud.google.com/bigtable

rockset.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

wiki.blazegraph.com

cloud.google.com/bigquery/docs

cloud.google.com/bigtable/docs

docs.rockset.com

Developer

Blazegraph

Google

Rockset

Initial release

2016

2006

2010

2015

2019

Current release

2.1.5, March 2019

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

extended commercial license available

commercial

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

Linux
OS X
Windows

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

yes

dynamic typing

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SPARQL is used as query language

yes

Read-only SQL queries, including JOINs

APIs and other access methods

CLI Client
RESTful HTTP API

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP REST

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

Atomic single-row operations

Concurrency

Support for concurrent manipulation of data

yes

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.

User concepts

Access control

yes

Security and Authentication via Web Application Container (Tomcat, Jetty)

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

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and organizations can be defined via Rockset console

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