DBMS > Amazon Redshift vs. Kyligence Enterprise vs. Lovefield vs. SiteWhere

System Properties Comparison Amazon Redshift vs. Kyligence Enterprise vs. Lovefield vs. SiteWhere

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Embeddable relational database for web apps written in pure JavaScript

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Time Series DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	0.44
Rank	#259	Overall
	#118	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Website

aws.amazon.com/redshift

kyligence.io/kyligence-enterprise

google.github.io/lovefield

github.com/sitewhere/sitewhere

Technical documentation

docs.aws.amazon.com/redshift

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

sitewhere1.sitewhere.io/index.html

Developer

Amazon (based on PostgreSQL)

Kyligence, Inc.

Google

SiteWhere

Initial release

2012

2016

2014

2010

Current release

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Common Public Attribution License Version 1.0

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

Java

JavaScript

Java

Server operating systems

hosted

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

Data scheme

yes

predefined scheme

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

ANSI SQL for queries (using Apache Calcite)

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on HBase

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

informational only, not enforced by the system

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

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.