DBMS > BigObject vs. H2 vs. Microsoft Azure SQL Database vs. MySQL vs. NCache

System Properties Comparison BigObject vs. H2 vs. Microsoft Azure SQL Database vs. MySQL vs. NCache

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Widely used open source RDBMS

Open-Source and Enterprise in-memory Key-Value Store

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Key/Value like access via memcached API

Key-value store

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Website

bigobject.io

www.h2database.com

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

www.mysql.com

www.alachisoft.com/ncache

Technical documentation

docs.bigobject.io

www.h2database.com/html/main.html

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

dev.mysql.com/doc

www.alachisoft.com/resources/docs

Developer

BigObject, Inc.

Thomas Mueller

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Alachisoft

Initial release

2015

2005

2010

1995

2005

Current release

2.2.220, July 2023

V12

8.4.0, April 2024

5.3.3, April 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Enterprise Edition 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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C++

C and C++

C#, .NET, .NET Core, 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

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

with proprietary extensions

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

Java

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

Lua

Java Stored Procedures and User-Defined Functions

Transact SQL

yes

proprietary syntax

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

With clustering: 2 database servers on different computers operate on identical copies of a database

yes, with always 3 replicas available

Multi-source replication
Source-replica replication

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

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Typical application scenarios

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Market metrics

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