DBMS > Graph Engine vs. Hive vs. Interbase

System Properties Comparison Graph Engine vs. Hive vs. Interbase

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Editorial information provided by DB-Engines

Name

Description

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

Light-weight proven RDBMS

originally from Borland

Primary database model

Graph DBMS
Key-value store

Relational DBMS

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

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	4.61
Rank	#72	Overall
	#39	Relational DBMS

Website

www.graphengine.io

hive.apache.org

www.embarcadero.com/products/interbase

Technical documentation

www.graphengine.io/docs/manual

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

docs.embarcadero.com/products/interbase

Developer

Microsoft

Apache Software Foundation

initially developed by Facebook

Embarcadero

Initial release

2010

2012

1984

Current release

3.1.3, April 2022

InterBase 2020, December 2019

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache Version 2

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

.NET and C

Java

Server operating systems

.NET

All OS with a Java VM

Android
iOS
Linux
OS X
Windows

Data scheme

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC

Supported programming languages

C#
C++
F#
Visual Basic

C++
Java
PHP
Python

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Interbase procedure and trigger language

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Interbase Change Views

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

Durability

Support for making data persistent

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
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