DBMS > AgensGraph vs. Lovefield vs. Netezza vs. Snowflake

System Properties Comparison AgensGraph vs. Lovefield vs. Netezza vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Embeddable relational database for web apps written in pure JavaScript

Data warehouse and analytics appliance part of IBM PureSystems

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

bitnine.net/agensgraph

google.github.io/lovefield

www.ibm.com/products/netezza

www.snowflake.com

Technical documentation

bitnine.net/documentation

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

docs.snowflake.net/manuals/index.html

Developer

Bitnine Global Inc.

Google

IBM

Snowflake Computing Inc.

Initial release

2016

2014

2000

2014

Current release

2.1, December 2018

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

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

Server operating systems

Linux
OS X
Windows

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

tested with Chrome, Firefox, IE, Safari

Linux

included in appliance

hosted

Data scheme

depending on used data model

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

JavaScript

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

Using read-only observers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

yes

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

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

Users with fine-grained authorization concept, user roles and pluggable authentication

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