DBMS > HugeGraph vs. Microsoft SQL Server vs. Oracle vs. Spark SQL vs. TypeDB

System Properties Comparison HugeGraph vs. Microsoft SQL Server vs. Oracle vs. Spark SQL vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Microsofts flagship relational DBMS

Widely used RDBMS

Spark SQL is a component on top of 'Spark Core' for structured data processing

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Graph DBMS

Relational DBMS

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.65
Rank	#234	Overall
	#20	Graph DBMS
	#107	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

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

www.oracle.com/database

spark.apache.org/sql

typedb.com

Technical documentation

hugegraph.apache.org/docs

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

docs.oracle.com/en/database

spark.apache.org/docs/latest/sql-programming-guide.html

typedb.com/docs

Developer

Baidu

Microsoft

Oracle

Apache Software Foundation

Vaticle

Initial release

2018

1989

1980

2014

2016

Current release

0.9

SQL Server 2022, November 2022

23c, September 2023

3.5.0 ( 2.13), September 2023

2.26.3, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

restricted free version is available

Open Source

Apache 2.0

Open Source

GPL Version 3, commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

C and C++

Scala

Java

Server operating systems

Linux
macOS
Unix

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Windows

Data scheme

yes

Schemaless in JSON and XML columns

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.

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

Groovy
Java
Python

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

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Java
Python
R
Scala

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

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

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

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

Sharding, horizontal partitioning

yes, utilizing Spark Core

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

none

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

can be realized in PL/SQL

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

substituted by the relationship feature

Transaction concepts

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

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Users, roles and permissions

fine grained access rights according to SQL-standard

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Licensing and pricing models

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