DBMS > HEAVY.AI vs. Microsoft Azure Cosmos DB vs. NuoDB vs. Oracle Berkeley DB

System Properties Comparison HEAVY.AI vs. Microsoft Azure Cosmos DB vs. NuoDB vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Globally distributed, horizontally scalable, multi-model database service

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Widely used in-process key-value store

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Spatial DBMS

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

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.99
Rank	#195	Overall
	#92	Relational DBMS

Score	2.52
Rank	#114	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

azure.microsoft.com/services/cosmos-db

www.3ds.com/nuodb-distributed-sql-database

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

Technical documentation

docs.heavy.ai

learn.microsoft.com/azure/cosmos-db

doc.nuodb.com

docs.oracle.com/cd/E17076_05/html/index.html

Developer

HEAVY.AI, Inc.

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2016

2014

2013

1994

Current release

5.10, January 2022

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

limited edition free

Open Source

commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++ and CUDA

C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

only with the Berkeley DB XML edition

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

JDBC
ODBC
Thrift
Vega

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

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

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

JavaScript

Java, SQL

Triggers

JavaScript

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Implicit feature of the cloud service

data is dynamically stored/cached on the nodes where it is read/written

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service

yes

Managed transparently by NuoDB

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Standard SQL roles/ privileges, Administrative Users

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