DBMS > Blazegraph vs. Hawkular Metrics vs. Kingbase vs. LeanXcale

System Properties Comparison Blazegraph vs. Hawkular Metrics vs. Kingbase vs. LeanXcale

Please select another system to include it in the comparison.

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.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Graph DBMS
RDF store

Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Website

Technical documentation

wiki.blazegraph.com

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

Blazegraph

Community supported by Red Hat

BeiJing KINGBASE Information technologies inc.

LeanXcale

Initial release

2006

2014

1999

2015

Current release

2.1.5, March 2019

V8.0, August 2021

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and Java

Server operating systems

Linux
OS X
Windows

Linux
Windows

Data scheme

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

Standard with numerous extensions

yes

through Apache Derby

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

HTTP REST

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Go
Java
Python
Ruby

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
Java
Scala

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning (by range, list and hash) and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

yes

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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)

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

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

Faster with GPUs: 5 turbocharged databases
26 September 2016, InfoWorld

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

Made in China 2025 is back, with a new name and a focus on database companies – The China Project
19 December 2022, The China Project

Opening preparation - Alekhine defense, Saemisch variation
18 April 2016, Chess.com

Backup & Recovery Solutions from China
4 August 2022, Хабр

provided by Google News

Share this page