DBMS > Amazon CloudSearch vs. Apache Impala vs. Drizzle vs. Microsoft Azure Cosmos DB

System Properties Comparison Amazon CloudSearch vs. Apache Impala vs. Drizzle vs. Microsoft Azure Cosmos DB

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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

Analytic DBMS for Hadoop

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

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Search engine

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

Spatial DBMS

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

aws.amazon.com/cloudsearch

impala.apache.org

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.aws.amazon.com/cloudsearch

impala.apache.org/impala-docs.html

learn.microsoft.com/azure/cosmos-db

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Drizzle project, originally started by Brian Aker

Microsoft

Initial release

2012

2013

2008

2014

Current release

4.1.0, June 2022

7.2.4, September 2012

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

GNU GPL

commercial

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++

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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.

Secondary indexes

yes

all search fields are automatically indexed

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

HTTP API

JDBC
ODBC

JDBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

JavaScript

Triggers

hooks for callbacks inside the server can be used.

JavaScript

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

selectable replication factor

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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.

User concepts

Access control

authentication via encrypted signatures

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights can be defined down to the item level

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