DBMS > Dgraph vs. GBase vs. Hawkular Metrics vs. IRONdb

System Properties Comparison Dgraph vs. GBase vs. Hawkular Metrics vs. IRONdb

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Distributed and scalable native Graph DBMS

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Primary database model

Graph DBMS

Relational DBMS

Time Series DBMS

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

Score	1.39
Rank	#155	Overall
	#15	Graph DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Website

dgraph.io

www.gbase.cn

www.hawkular.org

www.circonus.com/solutions/time-series-database/

Technical documentation

dgraph.io/docs

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

docs.circonus.com/irondb/category/getting-started

Developer

Dgraph Labs, Inc.

General Data Technology Co., Ltd.

Community supported by Red Hat

Circonus LLC.

Initial release

2016

2004

2014

2017

Current release

GBase 8a, GBase 8s, GBase 8c

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

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

C, Java, Python

Java

C and C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

Standard with numerous extensions

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
C API
JDBC
ODBC

HTTP REST

HTTP API

Supported programming languages

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

Go
Java
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

user defined functions

yes, in Lua

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

yes

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

Sharding

based on Cassandra

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

selectable replication factor

based on Cassandra

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

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.

User concepts

Access control

Planned for future releases

yes

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More resources

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