DBMS > BigObject vs. Microsoft Azure SQL Database vs. Oracle Coherence vs. YottaDB

System Properties Comparison BigObject vs. Microsoft Azure SQL Database vs. Oracle Coherence vs. YottaDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Database as a Service offering with high compatibility to Microsoft SQL Server

Oracles in-memory data grid solution

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

using the Octo plugin

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	0.28
Rank	#306	Overall
	#44	Key-value stores

Website

bigobject.io

azure.microsoft.com/en-us/products/azure-sql/database

www.oracle.com/java/coherence

yottadb.com

Technical documentation

docs.bigobject.io

docs.microsoft.com/en-us/azure/azure-sql

docs.oracle.com/en/middleware/standalone/coherence

yottadb.com/resources/documentation

Developer

BigObject, Inc.

Microsoft

Oracle

YottaDB, LLC

Initial release

2015

2010

2007

2001

Current release

V12

14.1, August 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

AGPL 3.0

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++

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)

hosted

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

SQL-like DML and DDL statements

yes

by using the Octo plugin

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

JCache
JPA
RESTful HTTP API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

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

.Net
C++
Java

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

Server-side scripts

Stored procedures

Lua

Transact SQL

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes, with always 3 replicas available

yes, with selectable consistency level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

configurable

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

optionally

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

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

Users and groups based on OS-security mechanisms

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More resources

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7 February 2017, Matthias Gelbmann

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