DBMS > BigObject vs. Hive vs. Oracle NoSQL vs. VelocityDB

System Properties Comparison BigObject vs. Hive vs. Oracle NoSQL vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Document store
Key-value store
Relational DBMS

Graph DBMS
Object oriented DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

bigobject.io

hive.apache.org

www.oracle.com/database/nosql/technologies/nosql

velocitydb.com

Technical documentation

docs.bigobject.io

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

velocitydb.com/UserGuide

Developer

BigObject, Inc.

Apache Software Foundation

initially developed by Facebook

Oracle

VelocityDB Inc

Initial release

2015

2012

2011

Current release

3.1.3, April 2022

23.3, December 2023

7.x

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache Version 2

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

All OS with a Java VM

Linux
Solaris SPARC/x86

Any that supports .NET

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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

SQL-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC
Thrift

RESTful HTTP API

.Net

Supported programming languages

C++
Java
PHP
Python

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net

Server-side scripts

Stored procedures

Lua

yes

user defined functions and integration of map-reduce

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

off heap cache

yes

User concepts

Access control

Access rights for users, groups and roles

Access rights for users and roles

Based on Windows Authentication

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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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