DBMS > ArcadeDB vs. Lovefield vs. Snowflake

System Properties Comparison ArcadeDB vs. Lovefield vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Embeddable relational database for web apps written in pure JavaScript

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

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

arcadedb.com

google.github.io/lovefield

www.snowflake.com

Technical documentation

docs.arcadedb.com

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

docs.snowflake.net/manuals/index.html

Developer

Arcade Data

Google

Snowflake Computing Inc.

Initial release

2021

2014

Current release

September 2021

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 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

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Implementation language

Java

JavaScript

Server operating systems

All OS with a Java VM

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

tested with Chrome, Firefox, IE, Safari

hosted

Data scheme

schema-free

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

SQL-like query language, no joins

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

CLI Client
JDBC
ODBC

Supported programming languages

Java

JavaScript

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

Using read-only observers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

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

relationship in graphs

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

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

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