DBMS > Amazon SimpleDB vs. Databricks vs. SAP HANA

System Properties Comparison Amazon SimpleDB vs. Databricks vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

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

Key-value store

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	1.83
Rank	#131	Overall
	#23	Key-value stores

Score	85.60
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	41.21
Rank	#22	Overall
	#15	Relational DBMS

Website

aws.amazon.com/simpledb

www.databricks.com

www.sap.com/products/hana.html

Technical documentation

docs.aws.amazon.com/simpledb

docs.databricks.com

help.sap.com/hana

Developer

Amazon

Databricks

SAP

Initial release

2007

2013

2010

Current release

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

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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Server operating systems

hosted

Appliance or cloud-service

Data scheme

schema-free

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 columns are indexed automatically

yes

SQL

Support of SQL

with Databricks SQL

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Python
R
Scala

Server-side scripts

Stored procedures

user defined functions and aggregates

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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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