DBMS > AlaSQL vs. H2 vs. Hawkular Metrics vs. HugeGraph vs. IBM Db2 warehouse

System Properties Comparison AlaSQL vs. H2 vs. Hawkular Metrics vs. HugeGraph vs. IBM Db2 warehouse

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Cloud-based data warehousing service

Primary database model

Document store
Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	1.30
Rank	#164	Overall
	#75	Relational DBMS

Website

alasql.org

www.h2database.com

www.hawkular.org

github.com/hugegraph
hugegraph.apache.org

www.ibm.com/products/db2/warehouse

Technical documentation

github.com/AlaSQL/alasql

www.h2database.com/html/main.html

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

hugegraph.apache.org/docs

Developer

Andrey Gershun & Mathias R. Wulff

Thomas Mueller

Community supported by Red Hat

Baidu

IBM

Initial release

2014

2005

2014

2018

2014

Current release

2.2.220, July 2023

0.9

License

Commercial or Open Source

Open Source

MIT-License

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

JavaScript

Java

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

All OS with a Java VM

Linux
OS X
Windows

Linux
macOS
Unix

hosted

Data scheme

schema-free

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.

Import/export of XML data possible

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

yes

APIs and other access methods

JavaScript API

JDBC
ODBC

HTTP REST

Java API
RESTful HTTP API
TinkerPop Gremlin

.NET Client API
JDBC
ODBC
OLE DB

Supported programming languages

JavaScript

Java

Go
Java
Python
Ruby

Groovy
Java
Python

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

asynchronous Gremlin script jobs

PL/SQL, SQL PL

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

yes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

With clustering: 2 database servers on different computers operate on identical copies of a database

selectable replication factor

based on Cassandra

yes

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

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

fine grained access rights according to SQL-standard

Users, roles and permissions

fine grained access rights according to SQL-standard

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