DBMS > Amazon DynamoDB vs. Cubrid vs. Google Cloud Bigtable vs. Interbase vs. NCache

System Properties Comparison Amazon DynamoDB vs. Cubrid vs. Google Cloud Bigtable vs. Interbase vs. NCache

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Light-weight proven RDBMS

originally from Borland

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

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Key-value store

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	5.04
Rank	#71	Overall
	#39	Relational DBMS

Score	0.98
Rank	#196	Overall
	#29	Key-value stores

Website

aws.amazon.com/dynamodb

cubrid.com (korean)
cubrid.org (english)

cloud.google.com/bigtable

www.embarcadero.com/products/interbase

www.alachisoft.com/ncache

Technical documentation

docs.aws.amazon.com/dynamodb

cubrid.org/manuals

cloud.google.com/bigtable/docs

docs.embarcadero.com/products/interbase

www.alachisoft.com/resources/docs

Developer

Amazon

CUBRID Corporation, CUBRID Foundation

Google

Embarcadero

Alachisoft

Initial release

2012

2008

2015

1984

2005

Current release

11.0, January 2021

InterBase 2020, December 2019

5.3.3, April 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

commercial

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.

Implementation language

C, C++, Java

C#, .NET, .NET Core, Java

Server operating systems

hosted

Linux
Windows

hosted

Android
iOS
Linux
OS X
Windows

Linux
Windows

Data scheme

schema-free

yes

schema-free

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

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

ADO.NET
JDBC
ODBC
OLE DB

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

ADO.NET
JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

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

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Interbase procedure and trigger language

support for stored procedures with SQL-Server CLR

Triggers

yes

by integration with AWS Lambda

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Internal replication in Colossus, and regional replication between two clusters in different zones

Interbase Change Views

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Atomic single-row operations

ACID

optimistic locking and pessimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

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

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

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Typical application scenarios

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Market metrics

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