DBMS > AlaSQL vs. Hawkular Metrics vs. InfinityDB vs. Infobright vs. Lovefield

System Properties Comparison AlaSQL vs. Hawkular Metrics vs. InfinityDB vs. Infobright vs. Lovefield

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

A Java embedded Key-Value Store which extends the Java Map interface

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

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Document store
Relational DBMS

Time Series DBMS

Key-value store

Relational 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	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

alasql.org

www.hawkular.org

boilerbay.com

ignitetech.com/softwarelibrary/infobrightdb

google.github.io/lovefield

Technical documentation

github.com/AlaSQL/alasql

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

boilerbay.com/infinitydb/manual

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Andrey Gershun & Mathias R. Wulff

Community supported by Red Hat

Boiler Bay Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Google

Initial release

2014

2002

2005

2014

Current release

4.0

2.1.12, February 2017

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache 2.0

commercial

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

Open Source

Apache 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

JavaScript

Java

JavaScript

Server operating systems

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

Linux
OS X
Windows

All OS with a Java VM

Linux
Windows

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

tested with Chrome, Firefox, IE, Safari

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

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

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JavaScript API

HTTP REST

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

ADO.NET
JDBC
ODBC

Supported programming languages

JavaScript

Go
Java
Python
Ruby

Java

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

JavaScript

Server-side scripts

Stored procedures

Triggers

yes

via Hawkular Alerting

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on Cassandra

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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