DBMS > HugeGraph vs. JSqlDb vs. LevelDB vs. Microsoft SQL Server vs. Sadas Engine

System Properties Comparison HugeGraph vs. JSqlDb vs. LevelDB vs. Microsoft SQL Server vs. Sadas Engine

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

A fast-speed and highly-scalable Graph DBMS

JavaScript Query Language Database, stores JavaScript objects and primitives

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Microsofts flagship relational DBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Graph DBMS

Document store
Object oriented DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

jsqldb.org (offline)

github.com/google/leveldb

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

www.sadasengine.com

Technical documentation

hugegraph.apache.org/docs

github.com/google/leveldb/blob/main/doc/index.md

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

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Baidu

Konrad von Backstrom

Google

Microsoft

SADAS s.r.l.

Initial release

2018

2011

1989

2006

Current release

0.9

0.8, December 2018

1.23, February 2021

SQL Server 2022, November 2022

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD

commercial

restricted free version is available

commercial

free trial version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Server operating systems

Linux
macOS
Unix

Linux
macOS
Windows

Illumos
Linux
OS X
Windows

Linux
Windows

AIX
Linux
Windows

Data scheme

yes

schema-free

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

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

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

JDBC
ODBC
Proprietary protocol

Supported programming languages

Groovy
Java
Python

JavaScript

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

functions in JavaScript

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

none

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

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

none

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

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

using RocksDB

yes

with automatic compression on writes

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Users, roles and permissions

fine grained access rights according to SQL-standard

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

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