DBMS > Oracle NoSQL vs. Stardog vs. SurrealDB vs. Tkrzw

System Properties Comparison Oracle NoSQL vs. Stardog vs. SurrealDB 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

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

A fully ACID transactional, developer-friendly, multi-model DBMS

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

Graph DBMS
RDF store

Document store
Graph DBMS

Key-value store

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	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

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

Website

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

www.stardog.com

surrealdb.com

dbmx.net/tkrzw

Technical documentation

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

docs.stardog.com

surrealdb.com/docs

Developer

Oracle

Stardog-Union

SurrealDB Ltd

Mikio Hirabayashi

Initial release

2011

2010

2022

2020

Current release

24.1, May 2024

7.3.0, May 2020

v1.5.0, May 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)

commercial

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

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

Rust

C++

Server operating systems

Linux
Solaris SPARC/x86

Linux
macOS
Windows

Linux
macOS

Data scheme

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

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like DML and DDL statements

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

SQL-like query language

APIs and other access methods

RESTful HTTP API

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

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Deno
Go
JavaScript (Node.js)
Rust

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

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

Sharding

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

Multi-source replication in HA-Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency in HA-Cluster

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 authentication and database rules

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