DBMS > Amazon SimpleDB vs. Google BigQuery vs. MariaDB vs. NCache vs. Oracle Coherence

System Properties Comparison Amazon SimpleDB vs. Google BigQuery vs. MariaDB vs. NCache vs. Oracle Coherence

Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Large scale data warehouse service with append-only tables

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

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

Oracles in-memory data grid solution

Primary database model

Key-value store

Relational DBMS

Key-value store

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	1.85
Rank	#138	Overall
	#24	Key-value stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

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

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

aws.amazon.com/simpledb

cloud.google.com/bigquery

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

www.alachisoft.com/ncache

www.oracle.com/java/coherence

Technical documentation

docs.aws.amazon.com/simpledb

cloud.google.com/bigquery/docs

mariadb.com/kb/en/library

www.alachisoft.com/resources/docs

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

Developer

Amazon

Google

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Alachisoft

Oracle

Initial release

2007

2010

2009

Fork of MySQL, which was first released in 1995

2005

2007

Current release

11.3.2, February 2024

5.3.3, April 2024

14.1, August 2023

License

Commercial or Open Source

commercial

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

Enterprise Edition available

commercial

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 C++

C#, .NET, .NET Core, Java

Java

Server operating systems

hosted

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Linux
Windows

All OS with a Java VM

Data scheme

schema-free

yes

Dynamic columns are supported

schema-free

Typing

predefined data types such as float or date

yes

partial

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

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

All columns are indexed automatically

yes

SQL

Support of SQL

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

RESTful HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

IDistributedCache
JCache
LINQ
Proprietary native API

JCache
JPA
RESTful HTTP API

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

.Net
C++
Java

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

PL/SQL compatibility added with version 10.3

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

none

several options for horizontal partitioning and Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Concurrent data updates can be detected by the application

Since BigQuery is designed for querying data

ACID

not for MyISAM storage engine

optimistic locking and pessimistic locking

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

not for in-memory storage engine

yes

optionally

In-memory capabilities

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

yes

with MEMORY storage engine

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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

authentification to access the cache via certificates or http basic authentication

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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