DBMS > Lovefield vs. Microsoft Azure Table Storage vs. Sadas Engine vs. Ultipa

System Properties Comparison Lovefield vs. Microsoft Azure Table Storage vs. Sadas Engine vs. Ultipa

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Editorial information provided by DB-Engines

Name

Description

Embeddable relational database for web apps written in pure JavaScript

A Wide Column Store for rapid development using massive semi-structured datasets

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

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

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

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

google.github.io/lovefield

azure.microsoft.com/en-us/services/storage/tables

www.sadasengine.com

www.ultipa.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

www.ultipa.com/document

Developer

Google

Microsoft

SADAS s.r.l.

Ultipa

Initial release

2014

2012

2006

2019

Current release

2.1.12, February 2017

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free trial version available

commercial

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

JavaScript

C++

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

hosted

AIX
Linux
Windows

Data scheme

yes

schema-free

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

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

Supported programming languages

JavaScript

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Access rights based on private key authentication or shared access signatures

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

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