DBMS > Oracle NoSQL vs. PostGIS vs. TigerGraph vs. Tkrzw

System Properties Comparison Oracle NoSQL vs. PostGIS vs. TigerGraph vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Spatial extension of PostgreSQL

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store
Key-value store
Relational DBMS

Spatial DBMS

Graph DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

www.oracle.com/database/nosql/technologies/nosql

postgis.net

www.tigergraph.com

dbmx.net/tkrzw

Technical documentation

docs.oracle.com/en/database/other-databases/nosql-database/index.html

postgis.net/documentation

docs.tigergraph.com

Developer

Oracle

Mikio Hirabayashi

Initial release

2011

2005

2017

2020

Current release

24.1, May 2024

3.4.2, February 2024

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

GPL v2.0

commercial

Open Source

Apache Version 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

Java

C++

Server operating systems

Linux
Solaris SPARC/x86

Linux

Linux
macOS

Data scheme

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

schema-free

Typing

predefined data types such as float or date

optional

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API

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

Supported programming languages

C
C#
Go
Java
JavaScript (Node.js)
Python

C++
Java

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

none

Replication methods

Methods for redundantly storing data on multiple nodes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

based on PostgreSQL

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

configurable

ACID within a storage node (=shard)

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

off heap cache

yes

using specific database classes

User concepts

Access control

Access rights for users and roles

yes

based on PostgreSQL

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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