DBMS > Blazegraph vs. DolphinDB vs. EJDB vs. Microsoft Azure Table Storage

System Properties Comparison Blazegraph vs. DolphinDB vs. EJDB vs. Microsoft Azure Table Storage

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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.

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

Primary database model

Graph DBMS
RDF store

Time Series DBMS
Vector DBMS

Document store

Wide column store

Secondary database models

Relational DBMS

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

Score	0.74
Rank	#217	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Website

blazegraph.com

www.dolphindb.com

github.com/Softmotions/ejdb

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

Technical documentation

wiki.blazegraph.com

docs.dolphindb.cn/en/help200/index.html

github.com/Softmotions/ejdb/blob/master/README.md

Developer

Blazegraph

DolphinDB, Inc

Softmotions

Microsoft

Initial release

2006

2018

2012

Current release

2.1.5, March 2019

v2.00.4, January 2022

License

Commercial or Open Source

Open Source

extended commercial license available

commercial

free community version available

Open Source

GPLv2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

server-less

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

yes

string, integer, double, bool, date, object_id

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

SQL-like query language

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

in-process shared library

RESTful HTTP API

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

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

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

Foreign keys

Referential integrity

yes

Relationships in Graphs

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

ACID

yes

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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.

yes

User concepts

Access control

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

Administrators, Users, Groups

Access rights based on private key authentication or shared access signatures

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More resources

Recent citations in the news

Video: Blazegraph Accelerates Graph Computing with GPUs
20 December 2015, insideHPC

This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines
19 August 2023, MarkTechPost

provided by Google News

How to use Azure Table storage in .Net
10 July 2024, InfoWorld

Working with Azure to Use and Manage Data Lakes
23 July 2024, Simplilearn

Azure Cosmos DB Data Migration tool imports from Azure Table storage
5 May 2015, azure.microsoft.com

How to Use C# Azure.Data.Tables SDK with Azure Cosmos DB
9 July 2021, hackernoon.com

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

provided by Google News

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