DBMS > Amazon Redshift vs. Amazon SimpleDB vs. Galaxybase vs. HEAVY.AI vs. Lovefield

System Properties Comparison Amazon Redshift vs. Amazon SimpleDB vs. Galaxybase vs. HEAVY.AI vs. Lovefield

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Scalable, ACID-compliant native distributed parallel graph platform

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

aws.amazon.com/redshift

aws.amazon.com/simpledb

galaxybase.com

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

google.github.io/lovefield

Technical documentation

docs.aws.amazon.com/redshift

docs.aws.amazon.com/simpledb

docs.heavy.ai

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

Developer

Amazon (based on PostgreSQL)

Amazon

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

HEAVY.AI, Inc.

Google

Initial release

2012

2007

2017

2016

2014

Current release

Nov 20, November 2021

5.10, January 2022

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

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

C and 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

Data scheme

yes

schema-free

Strong typed schema

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

restricted

yes

All columns are indexed automatically

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

JDBC
ODBC
Thrift
Vega

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Go
Java
Python

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Python

user defined procedures and functions

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding must be implemented in the application

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Concurrent data updates can be detected by the application

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

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Role-based access control

fine grained access rights according to SQL-standard

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