DBMS > Dgraph vs. GeoMesa vs. Lovefield vs. OushuDB vs. TigerGraph

System Properties Comparison Dgraph vs. GeoMesa vs. Lovefield vs. OushuDB vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Embeddable relational database for web apps written in pure JavaScript

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

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	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

dgraph.io

www.geomesa.org

google.github.io/lovefield

www.oushu.com/product/oushuDB

www.tigergraph.com

Technical documentation

dgraph.io/docs

www.geomesa.org/documentation/stable/user/index.html

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

www.oushu.com/documentation

docs.tigergraph.com

Developer

Dgraph Labs, Inc.

CCRi and others

Google

Oushu

Initial release

2016

2014

2017

Current release

5.0.0, May 2024

2.1.12, February 2017

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

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

Scala

JavaScript

C++

Server operating systems

Linux
OS X
Windows

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

tested with Chrome, Firefox, IE, Safari

Linux

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

Full-featured ANSI SQL support

SQL-like query language (GSQL)

APIs and other access methods

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

JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

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

JavaScript

C
C++

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on storage layer

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

depending on storage layer

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Foreign keys

Referential integrity

yes

Relationships in graphs

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.

depending on storage layer

yes

using MemoryDB

User concepts

Access control

Planned for future releases

yes

depending on the DBMS used for storage

Kerberos, SSL and role based access

Role-based access control

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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