DBMS > Amazon DynamoDB vs. Cubrid vs. Drizzle vs. GigaSpaces vs. Google Cloud Bigtable

System Properties Comparison Amazon DynamoDB vs. Cubrid vs. Drizzle vs. GigaSpaces vs. Google Cloud Bigtable

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

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

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store
Wide column store

Secondary database models

Graph DBMS
Search engine

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	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

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

Website

aws.amazon.com/dynamodb

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

www.gigaspaces.com

cloud.google.com/bigtable

Technical documentation

docs.aws.amazon.com/dynamodb

cubrid.org/manuals

docs.gigaspaces.com/latest/landing.html

cloud.google.com/bigtable/docs

Developer

Amazon

CUBRID Corporation, CUBRID Foundation

Drizzle project, originally started by Brian Aker

Gigaspaces Technologies

Google

Initial release

2012

2008

2000

2015

Current release

11.0, January 2021

7.2.4, September 2012

15.5, September 2020

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

Open Source

GNU GPL

Open Source

Apache Version 2; Commercial licenses 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, C++, Java

C++

Java, C++, .Net

Server operating systems

hosted

Linux
Windows

FreeBSD
Linux
OS X

Linux
macOS
Solaris
Windows

hosted

Data scheme

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-99 for query and DML statements

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

JDBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

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

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++
Java
PHP

.Net
C++
Java
Python
Scala

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

hooks for callbacks inside the server can be used.

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

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

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

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

Concurrency

Support for concurrent manipulation of data

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Role-based access control

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

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