DBMS > Dgraph vs. LevelDB vs. OushuDB vs. TigerGraph vs. TimesTen

System Properties Comparison Dgraph vs. LevelDB vs. OushuDB vs. TigerGraph vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

In-Memory RDBMS compatible to Oracle

Primary database model

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

dgraph.io

github.com/google/leveldb

www.oushu.com/product/oushuDB

www.tigergraph.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

dgraph.io/docs

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

www.oushu.com/documentation

docs.tigergraph.com

docs.oracle.com/database/timesten-18.1

Developer

Dgraph Labs, Inc.

Google

Oushu

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2016

2011

2017

1998

Current release

1.23, February 2021

4.0.1, August 2020

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

commercial

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

C++

Server operating systems

Linux
OS X
Windows

Illumos
Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

Full-featured ANSI SQL support

SQL-like query language (GSQL)

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C++

C++
Java

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

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

with automatic compression on writes

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

Planned for future releases

Kerberos, SSL and role based access

Role-based access control

fine grained access rights according to SQL-standard

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