DBMS > AlaSQL vs. Amazon Redshift vs. Hawkular Metrics vs. Ignite vs. Infobright

System Properties Comparison AlaSQL vs. Amazon Redshift vs. Hawkular Metrics vs. Ignite vs. Infobright

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Large scale data warehouse service for use with business intelligence tools

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	0.49
Rank	#259	Overall
	#40	Document stores
	#120	Relational DBMS

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.04
Rank	#374	Overall
	#38	Time Series DBMS

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	1.00
Rank	#193	Overall
	#90	Relational DBMS

Website

alasql.org

aws.amazon.com/redshift

www.hawkular.org

ignite.apache.org

ignitetech.com/softwarelibrary/infobrightdb

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/redshift

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

apacheignite.readme.io/docs

Developer

Andrey Gershun & Mathias R. Wulff

Amazon (based on PostgreSQL)

Community supported by Red Hat

Apache Software Foundation

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2014

2012

2014

2015

2005

Current release

Apache Ignite 2.6

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

C++, Java, .Net

Server operating systems

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

hosted

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux
Windows

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.

yes

Secondary indexes

restricted

yes

Knowledge Grid Technology used instead

SQL

Support of SQL

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

yes

does not fully support an SQL-standard

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

yes

APIs and other access methods

JavaScript API

JDBC
ODBC

HTTP REST

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

ADO.NET
JDBC
ODBC

Supported programming languages

JavaScript

All languages supporting JDBC/ODBC

Go
Java
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

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

Triggers

yes

via Hawkular Alerting

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

selectable replication factor

based on Cassandra

yes (replicated cache)

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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