DBMS > Amazon DynamoDB vs. Cubrid vs. Drizzle vs. Google Cloud Bigtable vs. Manticore Search

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

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.

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

Multi-storage database for search, including full-text search.

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store
Wide column store

Search engine

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	87.26
Rank	#15	Overall
	#2	Document stores
	#2	Key-value stores

Score	1.24
Rank	#158	Overall
	#75	Relational DBMS

Score	4.84
Rank	#80	Overall
	#13	Key-value stores
	#6	Wide column stores

Score	0.11
Rank	#316	Overall
	#20	Search engines

Website

aws.amazon.com/dynamodb

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

cloud.google.com/bigtable

manticoresearch.com

Technical documentation

docs.aws.amazon.com/dynamodb

cubrid.org/manuals

cloud.google.com/bigtable/docs

manual.manticoresearch.com

Developer

Amazon

CUBRID Corporation, CUBRID Foundation

Drizzle project, originally started by Brian Aker

Google

Manticore Software

Initial release

2012

2008

2015

2017

Current release

11.0, January 2021

7.2.4, September 2012

4.2, December 2021

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

commercial

Open Source

GPL version 2

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

C++

Server operating systems

hosted

Linux
Windows

FreeBSD
Linux
OS X

hosted

FreeBSD
Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

Fixed schema

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

JDBC

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

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

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

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication
Source-replica replication

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

Synchronous replication based on Galera library

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)

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

yes

isolated transactions for atomic changes and binary logging for safe writes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

In-memory capabilities

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

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

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

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