DBMS > Blazegraph vs. GridGain vs. Teradata Aster vs. WakandaDB

System Properties Comparison Blazegraph vs. GridGain vs. Teradata Aster vs. WakandaDB

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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.

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

GridGain is an in-memory computing platform, built on Apache Ignite

Platform for big data analytics on multistructured data sources and types

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Graph DBMS
RDF store

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Object oriented 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	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

blazegraph.com

www.gridgain.com

wakanda.github.io

Technical documentation

wiki.blazegraph.com

www.gridgain.com/docs/index.html

wakanda.github.io/doc

Developer

Blazegraph

GridGain Systems, Inc.

Teradata

Wakanda SAS

Initial release

2006

2007

2005

2012

Current release

2.1.5, March 2019

GridGain 8.5.1

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

extended commercial license available

commercial, open source

commercial

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, C++, .Net, Python, REST, SQL

C++, JavaScript

Server operating systems

Linux
OS X
Windows

Linux
OS X
Solaris
Windows
z/OS

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

yes

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Java
Python
R

JavaScript

Server-side scripts

Stored procedures

yes

yes (compute grid and cache interceptors can be used instead)

R packages

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

Transaction concepts

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

ACID

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.

yes

User concepts

Access control

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

Role-based access control
Security Hooks for custom implementations

fine grained access rights according to SQL-standard

yes

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More resources

Recent citations in the news

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

Harnessing GPUs Delivers a Big Speedup for Graph Analytics
15 December 2015, Datanami

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

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GridGain Advances Its Unified Real-Time Data Platform to Help Enterprises Accelerate AI-Driven Data Processing
10 July 2024, insideBIGDATA

GridGain Sponsoring Strategic AI and Kafka Conferences This Month
4 September 2024, Datanami

GridGain in-memory data and generative AI
10 May 2024, Blocks & Files

Data Management News for the Week of July 12; Updates from Cloudera, HerculesAI, Oracle & More
12 July 2024, Solutions Review

Lalit Ahuja
13 August 2024, Forbes

provided by Google News

Northwestern Analytics Partners with Teradata Aster to Host Hackathon
23 May 2014, Northwestern Engineering

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Teradata Integrates Big Data Analytic Architecture
22 October 2012, PR Newswire

An American Dream Story, With A Silicon Valley Twist
14 August 2013, Forbes

Gartner, IBM, Teradata make Big Data announcements
17 October 2012, ZDNet

provided by Google News

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