DBMS > AlaSQL vs. Infobright vs. Netezza vs. RavenDB

System Properties Comparison AlaSQL vs. Infobright vs. Netezza vs. RavenDB

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

Data warehouse and analytics appliance part of IBM PureSystems

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

alasql.org

ignitetech.com/softwarelibrary/infobrightdb

www.ibm.com/products/netezza

ravendb.net

Technical documentation

github.com/AlaSQL/alasql

ravendb.net/docs

Developer

Andrey Gershun & Mathias R. Wulff

Ignite Technologies Inc.; formerly InfoBright Inc.

IBM

Hibernating Rhinos

Initial release

2014

2005

2000

2010

Current release

5.4, July 2022

License

Commercial or Open Source

Open Source

MIT-License

commercial

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

commercial

Open Source

AGPL version 3, commercial license available

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

Server operating systems

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

Linux
Windows

Linux

included in appliance

Linux
macOS
Raspberry Pi
Windows

Data scheme

schema-free

yes

schema-free

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

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 (RQL)

APIs and other access methods

JavaScript API

ADO.NET
JDBC
ODBC

JDBC
ODBC
OLE DB

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

JavaScript

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

C
C++
Fortran
Java
Lua
Perl
Python
R

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

ACID, Cluster-wide transaction available

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

exploiting MySQL or PostgreSQL frontend capabilities

Users with fine-grained authorization concept

Authorization levels configured per client per database

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