DBMS > Databricks vs. HugeGraph vs. PostGIS vs. Stardog

System Properties Comparison Databricks vs. HugeGraph vs. PostGIS vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

A fast-speed and highly-scalable Graph DBMS

Spatial extension of PostgreSQL

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Document store
Relational DBMS

Graph DBMS

Spatial DBMS

Graph DBMS
RDF store

Secondary database models

Relational DBMS

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

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.databricks.com

github.com/hugegraph
hugegraph.apache.org

postgis.net

www.stardog.com

Technical documentation

docs.databricks.com

hugegraph.apache.org/docs

postgis.net/documentation

docs.stardog.com

Developer

Databricks

Baidu

Stardog-Union

Initial release

2013

2018

2005

2010

Current release

0.9

3.4.2, February 2024

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL v2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Server operating systems

hosted

Linux
macOS
Unix

Linux
macOS
Windows

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

also supports composite index and range index

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

with Databricks SQL

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

Python
R
Scala

Groovy
Java
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

asynchronous Gremlin script jobs

user defined functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

based on PostgreSQL

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

based on PostgreSQL

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

edges in graph

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users, roles and permissions

yes

based on PostgreSQL

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

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Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

Exclusive | Pete Sonsini, Early Investor in Databricks, Gets Closer to Launching New VC Firm
3 May 2024, The Wall Street Journal

New AI Copyright Class Actions Target Nvidia, Databricks
4 May 2024, Law360

Databricks Achieves FedRAMP High Agency Authority to Operate for AWS GovCloud USA - English
30 April 2024, PR Newswire

Nvidia, Databricks Sued in Latest AI Copyright Class Actions
3 May 2024, Bloomberg Law

Tableau adds generative AI tools, tightens Databricks bond
30 April 2024, TechTarget

provided by Google News

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

provided by Google News

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