DBMS > Dgraph vs. Google BigQuery vs. LMDB vs. Lovefield

System Properties Comparison Dgraph vs. Google BigQuery vs. LMDB vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Large scale data warehouse service with append-only tables

A high performant, light-weight, embedded key-value database library

Embeddable relational database for web apps written in pure JavaScript

Primary database model

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

dgraph.io

cloud.google.com/bigquery

www.symas.com/symas-embedded-database-lmdb

google.github.io/lovefield

Technical documentation

dgraph.io/docs

cloud.google.com/bigquery/docs

www.lmdb.tech/doc

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

Developer

Dgraph Labs, Inc.

Google

Symas

Google

Initial release

2016

2010

2011

2014

Current release

0.9.32, January 2024

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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

hosted

Linux
Unix
Windows

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

tested with Chrome, Firefox, IE, Safari

Data scheme

schema-free

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

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/JSON API

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

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

Since BigQuery is designed for querying 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

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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