DBMS > Microsoft SQL Server vs. OceanBase vs. RDF4J vs. SurrealDB

System Properties Comparison Microsoft SQL Server vs. OceanBase vs. RDF4J vs. SurrealDB

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Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

A distributed, high available RDBMS compatible with Oracle and MySQL

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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

Primary database model

Relational DBMS

RDF store

Document store
Graph DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Wide column store

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

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	1.97
Rank	#119	Overall
	#58	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	1.11
Rank	#174	Overall
	#30	Document stores
	#17	Graph DBMS

Website

www.microsoft.com/en-us/sql-server

en.oceanbase.com

rdf4j.org

surrealdb.com

Technical documentation

learn.microsoft.com/en-US/sql/sql-server

en.oceanbase.com/docs/oceanbase-database

rdf4j.org/documentation

surrealdb.com/docs

Developer

Microsoft

OceanBase

previously Alibaba and Ant Group

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

SurrealDB Ltd

Initial release

1989

2010

2004

2022

Current release

SQL Server 2022, November 2022

4.3.0, April 2024

v1.5.0, May 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Rust

Server operating systems

Linux
Windows

Linux

Linux
OS X
Unix
Windows

Linux
macOS
Windows

Data scheme

yes

RDF Schemas

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Java
PHP
Python

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

Multi-source replication using Paxos

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

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

yes, based on authentication and database rules

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