DBMS > Amazon Redshift vs. Graph Engine vs. Hypertable vs. LokiJS

System Properties Comparison Amazon Redshift vs. Graph Engine vs. Hypertable vs. LokiJS

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

An open source BigTable implementation based on distributed file systems such as Hadoop

In-memory JavaScript DBMS

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Wide column store

Document store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.43
Rank	#264	Overall
	#42	Document stores

Website

aws.amazon.com/redshift

www.graphengine.io

github.com/techfort/LokiJS

Technical documentation

docs.aws.amazon.com/redshift

www.graphengine.io/docs/manual

techfort.github.io/LokiJS

Developer

Amazon (based on PostgreSQL)

Microsoft

Hypertable Inc.

Initial release

2012

2010

2009

2014

Current release

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

GNU version 3. Commercial license available

Open Source

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

.NET and C

C++

JavaScript

Server operating systems

hosted

.NET

Linux
OS X
Windows

an inofficial Windows port is available

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

Data scheme

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

restricted

only exact value or prefix value scans

yes

via views

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

C++ API
Thrift

JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
F#
Visual Basic

C++
Java
Perl
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Python

yes

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor on file system level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

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