DBMS > EXASOL vs. Graph Engine vs. Hawkular Metrics vs. HugeGraph

System Properties Comparison EXASOL vs. Graph Engine vs. Hawkular Metrics vs. HugeGraph

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Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

A fast-speed and highly-scalable Graph DBMS

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Time Series DBMS

Graph DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Website

www.exasol.com

www.graphengine.io

www.hawkular.org

github.com/hugegraph
hugegraph.apache.org

Technical documentation

www.exasol.com/resources

www.graphengine.io/docs/manual

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

hugegraph.apache.org/docs

Developer

Exasol

Microsoft

Community supported by Red Hat

Baidu

Initial release

2000

2010

2014

2018

Current release

0.9

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

.NET and C

Java

Server operating systems

.NET

Linux
OS X
Windows

Linux
macOS
Unix

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

also supports composite index and range index

SQL

Support of SQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

RESTful HTTP API

HTTP REST

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

Java
Lua
Python
R

C#
C++
F#
Visual Basic

Go
Java
Python
Ruby

Groovy
Java
Python

Server-side scripts

Stored procedures

user defined functions

yes

asynchronous Gremlin script jobs

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

based on Cassandra

yes

depending on used storage backend, e.g. Cassandra and HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Access rights for users, groups and roles according to SQL-standard

Users, roles and permissions

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