DBMS > Dgraph vs. Graph Engine vs. Interbase vs. Lovefield

System Properties Comparison Dgraph vs. Graph Engine vs. Interbase vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

Light-weight proven RDBMS

originally from Borland

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Graph DBMS

Graph DBMS
Key-value store

Relational DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

dgraph.io

www.graphengine.io

www.embarcadero.com/products/interbase

google.github.io/lovefield

Technical documentation

dgraph.io/docs

www.graphengine.io/docs/manual

docs.embarcadero.com/products/interbase

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

Developer

Dgraph Labs, Inc.

Microsoft

Embarcadero

Google

Initial release

2016

2010

1984

2014

Current release

InterBase 2020, December 2019

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

.NET and C

JavaScript

Server operating systems

Linux
OS X
Windows

.NET

Android
iOS
Linux
OS X
Windows

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

tested with Chrome, Firefox, IE, Safari

Data scheme

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

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

C#
C++
F#
Visual Basic

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

JavaScript

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

yes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Interbase Change Views

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

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

Planned for future releases

fine grained access rights according to SQL-standard

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More resources

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