DBMS > Amazon CloudSearch vs. Apache Doris vs. Databricks vs. SAP HANA

System Properties Comparison Amazon CloudSearch vs. Apache Doris vs. Databricks vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

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

An MPP-based analytics DBMS embracing the MySQL protocol

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Search engine

Relational DBMS

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

aws.amazon.com/cloudsearch

doris.apache.org
github.com/apache/doris

www.databricks.com

www.sap.com/products/hana.html

Technical documentation

docs.aws.amazon.com/cloudsearch

github.com/apache/doris/wiki

docs.databricks.com

help.sap.com/hana

Developer

Amazon

Apache Software Foundation, originally contributed from Baidu

Databricks

SAP

Initial release

2012

2017

2013

2010

Current release

1.2.2, February 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

hosted

Linux

hosted

Appliance or cloud-service

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

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 Databricks SQL

yes

APIs and other access methods

HTTP API

JDBC
MySQL client

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

Java

Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

user defined functions and aggregates

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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