DBMS > 4D vs. Amazon DynamoDB vs. Databricks vs. SQream DB vs. TimesTen

System Properties Comparison 4D vs. Amazon DynamoDB vs. Databricks vs. SQream DB vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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.

a GPU-based, columnar RDBMS for big data analytics workloads

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Document store
Key-value store

Document store
Relational DBMS

Relational DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

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

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.4d.com

aws.amazon.com/dynamodb

www.databricks.com

sqream.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

developer.4d.com

docs.aws.amazon.com/dynamodb

docs.databricks.com

docs.sqream.com

docs.oracle.com/database/timesten-18.1

Developer

4D, Inc

Amazon

Databricks

SQream Technologies

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1984

2012

2013

2017

1998

Current release

v20, April 2023

2022.1.6, December 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

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++, CUDA, Haskell, Java, Scala

Server operating systems

OS X
Windows

hosted

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

schema-free

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

SQL

Support of SQL

yes

close to SQL 92

with Databricks SQL

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

.Net
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

4D proprietary IDE
PHP

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Python
R
Scala

C++
Java
JavaScript (Node.js)
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

user defined functions in Python

PL/SQL

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Users and groups

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

fine grained access rights according to SQL-standard

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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