DBMS > Blazegraph vs. Microsoft Azure Table Storage vs. Pinecone vs. Transbase

System Properties Comparison Blazegraph vs. Microsoft Azure Table Storage vs. Pinecone vs. Transbase

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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.

A Wide Column Store for rapid development using massive semi-structured datasets

A managed, cloud-native vector database

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

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	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

blazegraph.com

azure.microsoft.com/en-us/services/storage/tables

www.pinecone.io

www.transaction.de/en/products/transbase.html

Technical documentation

wiki.blazegraph.com

docs.pinecone.io/docs/overview

www.transaction.de/en/products/transbase/features.html

Developer

Blazegraph

Microsoft

Pinecone Systems, Inc

Transaction Software GmbH

Initial release

2006

2012

2019

1987

Current release

2.1.5, March 2019

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

free development license

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 and C++

Server operating systems

Linux
OS X
Windows

hosted

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

String, Number, Boolean

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.

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

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

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

Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Transaction concepts

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

ACID

optimistic locking

yes

Concurrency

Support for concurrent manipulation of data

yes

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)

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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2 June 2023, Matthias Gelbmann

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