DBMS > Blazegraph vs. Brytlyt vs. Google BigQuery vs. IBM Cloudant

System Properties Comparison Blazegraph vs. Brytlyt vs. Google BigQuery vs. IBM Cloudant

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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

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

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Large scale data warehouse service with append-only tables

Database as a Service offering based on Apache CouchDB

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store

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

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Website

blazegraph.com

brytlyt.io

cloud.google.com/bigquery

www.ibm.com/products/cloudant

Technical documentation

wiki.blazegraph.com

docs.brytlyt.io

cloud.google.com/bigquery/docs

cloud.ibm.com/docs/Cloudant

Developer

Blazegraph

Brytlyt

Google

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Initial release

2006

2016

2010

Current release

2.1.5, March 2019

5.0, August 2023

License

Commercial or Open Source

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

Java

C, C++ and CUDA

Erlang

Server operating systems

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

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

yes

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

in PL/pgSQL

user defined functions

in JavaScript

View functions (Map-Reduce) in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication
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 or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

Durability

Support for making data persistent

yes

In-memory capabilities

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

Access rights for users can be defined per database

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