DBMS > Amazon CloudSearch vs. Amazon Redshift vs. Databricks vs. SpaceTime

System Properties Comparison Amazon CloudSearch vs. Amazon Redshift vs. Databricks vs. SpaceTime

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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

Large scale data warehouse service for use with business intelligence tools

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.

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Search engine

Relational DBMS

Document store
Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	1.85
Rank	#137	Overall
	#12	Search engines

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

aws.amazon.com/cloudsearch

aws.amazon.com/redshift

www.databricks.com

www.mireo.com/spacetime

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.aws.amazon.com/redshift

docs.databricks.com

Developer

Amazon

Amazon (based on PostgreSQL)

Databricks

Mireo

Initial release

2012

2013

2020

License

Commercial or Open Source

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++

Server operating systems

hosted

Linux

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

with Databricks SQL

A subset of ANSI SQL is implemented

APIs and other access methods

HTTP API

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Python
R
Scala

C#
C++
Python

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions and aggregates

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

Real-time block device replication (DRBD)

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

informational only, not enforced by the system

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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