DBMS > GBase vs. Graph Engine vs. Hive vs. YottaDB

System Properties Comparison GBase vs. Graph Engine vs. Hive vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

Technical documentation

www.graphengine.io/docs/manual

cwiki.apache.org/confluence/display/Hive/Home

yottadb.com/resources/documentation

Developer

General Data Technology Co., Ltd.

Microsoft

Apache Software Foundation

initially developed by Facebook

YottaDB, LLC

Initial release

2004

2010

2012

2001

Current release

GBase 8a, GBase 8s, GBase 8c

3.1.3, April 2022

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache Version 2

Open Source

AGPL 3.0

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, Java, Python

.NET and C

Java

Server operating systems

Linux

.NET

All OS with a Java VM

Docker
Linux

Data scheme

yes

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

Standard with numerous extensions

SQL-like DML and DDL statements

by using the Octo plugin

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

RESTful HTTP API

JDBC
ODBC
Thrift

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

C#
C++
F#
Visual Basic

C++
Java
PHP
Python

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

yes

Access rights for users, groups and roles

Users and groups based on OS-security mechanisms

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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