DBMS > 4D vs. Amazon Redshift vs. Google Cloud Bigtable vs. Rockset vs. TimesTen

System Properties Comparison 4D vs. Amazon Redshift vs. Google Cloud Bigtable vs. Rockset vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Large scale data warehouse service for use with business intelligence tools

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A scalable, reliable search and analytics service in the cloud, built on RocksDB

In-Memory RDBMS compatible to Oracle

Primary database model

Relational DBMS

Key-value store
Wide column store

Document store

Relational DBMS

Secondary database models

Relational DBMS
Search engine

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.4d.com

aws.amazon.com/redshift

cloud.google.com/bigtable

rockset.com

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

Technical documentation

developer.4d.com

docs.aws.amazon.com/redshift

cloud.google.com/bigtable/docs

docs.rockset.com

docs.oracle.com/database/timesten-18.1

Developer

4D, Inc

Amazon (based on PostgreSQL)

Google

Rockset

Oracle, TimesTen Performance Software, HP

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

Initial release

1984

2012

2015

2019

1998

Current release

v20, April 2023

11 Release 2 (11.2.2.8.0)

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

OS X
Windows

hosted

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

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

restricted

all fields are automatically indexed

yes

SQL

Support of SQL

yes

close to SQL 92

yes

does not fully support an SQL-standard

Read-only SQL queries, including JOINs

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP REST

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC

C#
C++
Go
Java
JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

user defined functions

in Python

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Atomic single-row operations

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and organizations can be defined via Rockset console

fine grained access rights according to SQL-standard

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