DBMS > Graph Engine vs. Lovefield vs. Spark SQL

System Properties Comparison Graph Engine vs. Lovefield vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Graph DBMS
Key-value store

Relational DBMS

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

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

www.graphengine.io

google.github.io/lovefield

spark.apache.org/sql

Technical documentation

www.graphengine.io/docs/manual

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

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Microsoft

Google

Apache Software Foundation

Initial release

2010

2014

Current release

2.1.12, February 2017

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

.NET and C

JavaScript

Scala

Server operating systems

.NET

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

tested with Chrome, Firefox, IE, Safari

Linux
OS X
Windows

Data scheme

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

SQL-like DML and DDL statements

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C#
C++
F#
Visual Basic

JavaScript

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

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

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More resources

Recent citations in the news

Trinity
2 June 2023, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

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