DBMS > Amazon CloudSearch vs. Apache Kylin vs. HEAVY.AI vs. Lovefield vs. SQLite

System Properties Comparison Amazon CloudSearch vs. Apache Kylin vs. HEAVY.AI vs. Lovefield vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

Widely used embeddable, in-process RDBMS

Primary database model

Search engine

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/cloudsearch

kylin.apache.org

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

www.sqlite.org

Technical documentation

docs.aws.amazon.com/cloudsearch

kylin.apache.org/docs

docs.heavy.ai

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

www.sqlite.org/docs.html

Developer

Amazon

Apache Software Foundation, originally contributed from eBay Inc

HEAVY.AI, Inc.

Google

Dwayne Richard Hipp

Initial release

2012

2015

2016

2014

2000

Current release

3.1.0, July 2020

5.10, January 2022

2.1.12, February 2017

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

Open Source

Public Domain

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

C++ and CUDA

JavaScript

Server operating systems

hosted

Linux

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

tested with Chrome, Firefox, IE, Safari

server-less

Data scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

SQL-like query language

via JavaScript builder pattern

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Multi-source 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

via file-system locks

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

User concepts

Access control

authentication via encrypted signatures

fine grained access rights according to SQL-standard

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