DBMS > HugeGraph vs. ITTIA vs. LevelDB vs. Oracle vs. Sadas Engine

System Properties Comparison HugeGraph vs. ITTIA vs. LevelDB vs. Oracle vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

Edge Time Series DBMS with Real-Time Stream Processing

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

Widely used RDBMS

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

Primary database model

Secondary database models

Relational 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	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

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

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.ittia.com

github.com/google/leveldb

www.oracle.com/database

www.sadasengine.com

Technical documentation

hugegraph.apache.org/docs

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

docs.oracle.com/en/database

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

Developer

Baidu

ITTIA L.L.C.

Google

Oracle

SADAS s.r.l.

Initial release

2018

2007

2011

1980

2006

Current release

0.9

8.7

1.23, February 2021

23c, September 2023

8.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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)

Database as a Service

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Implementation language

Java

C and C++

C++

C and C++

C++

Server operating systems

Linux
macOS
Unix

Linux
Windows

Illumos
Linux
OS X
Windows

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

AIX
Linux
Windows

Data scheme

yes

Fixed schema

schema-free

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

yes

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
RESTful HTTP API
WebSocket

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

JDBC
ODBC
Proprietary protocol

Supported programming languages

Groovy
Java
Python

C
C++
JavaScript (Node.js)
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

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

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

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

none

Sharding, horizontal partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

yes

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

can be realized in PL/SQL

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

yes

ACID

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

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

yes

managed by 'Learn by Usage'

User concepts

Access control

Users, roles and permissions

Database file passwords

fine grained access rights according to SQL-standard

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

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