DBMS > 4D vs. atoti vs. Google BigQuery vs. InfinityDB

System Properties Comparison 4D vs. atoti vs. Google BigQuery vs. InfinityDB

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Large scale data warehouse service with append-only tables

A Java embedded Key-Value Store which extends the Java Map interface

Primary database model

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Website

www.4d.com

atoti.io

cloud.google.com/bigquery

boilerbay.com

Technical documentation

developer.4d.com

docs.atoti.io

cloud.google.com/bigquery/docs

boilerbay.com/infinitydb/manual

Developer

4D, Inc

ActiveViam

Google

Boiler Bay Inc.

Initial release

1984

2010

2002

Current release

v20, April 2023

4.0

License

Commercial or Open Source

commercial

free versions available

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

Java

Server operating systems

OS X
Windows

hosted

All OS with a Java VM

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes

close to SQL 92

Multidimensional Expressions (MDX)

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

RESTful HTTP/JSON API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Supported programming languages

4D proprietary IDE
PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

Server-side scripts

Stored procedures

yes

Python

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Optimistic locking for transactions; no isolation for bulk loads

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Users and groups

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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