DBMS > Infobright vs. Kyligence Enterprise vs. Lovefield vs. Sadas Engine

System Properties Comparison Infobright vs. Kyligence Enterprise vs. Lovefield vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

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

A distributed analytics engine for big data, built on top of Apache Kylin

Embeddable relational database for web apps written in pure JavaScript

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

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

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

ignitetech.com/softwarelibrary/infobrightdb

kyligence.io/kyligence-enterprise

google.github.io/lovefield

www.sadasengine.com

Technical documentation

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Ignite Technologies Inc.; formerly InfoBright Inc.

Kyligence, Inc.

Google

SADAS s.r.l.

Initial release

2005

2016

2014

2006

Current release

2.1.12, February 2017

8.0

License

Commercial or Open Source

commercial

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

commercial

Open Source

Apache 2.0

commercial

free trial version 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

Java

JavaScript

C++

Server operating systems

Linux
Windows

Linux

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

tested with Chrome, Firefox, IE, Safari

AIX
Linux
Windows

Data scheme

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

JavaScript

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

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

yes

In-memory capabilities

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

yes

using MemoryDB

yes

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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

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More resources

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provided by Google News

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