DBMS > Amazon CloudSearch vs. Drizzle vs. GridGain vs. Snowflake

System Properties Comparison Amazon CloudSearch vs. Drizzle vs. GridGain vs. Snowflake

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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

A hosted search engine service by Amazon with the data stored in Amazons cloud

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

GridGain is an in-memory computing platform, built on Apache Ignite

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Search engine

Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

aws.amazon.com/cloudsearch

www.gridgain.com

www.snowflake.com

Technical documentation

docs.aws.amazon.com/cloudsearch

www.gridgain.com/docs/index.html

docs.snowflake.net/manuals/index.html

Developer

Amazon

Drizzle project, originally started by Brian Aker

GridGain Systems, Inc.

Snowflake Computing Inc.

Initial release

2012

2008

2007

2014

Current release

7.2.4, September 2012

GridGain 8.5.1

License

Commercial or Open Source

commercial

Open Source

GNU GPL

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++

Java, C++, .Net

Server operating systems

hosted

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

hosted

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

yes

with proprietary extensions

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

HTTP API

JDBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

CLI Client
JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes (cache interceptors and events)

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Multi-source replication
Source-replica replication

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

authentication via encrypted signatures

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Security Hooks for custom implementations

Users with fine-grained authorization concept, user roles and pluggable authentication

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