DBMS > 4D vs. HBase vs. InfinityDB vs. Spark SQL

System Properties Comparison 4D vs. HBase vs. InfinityDB vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

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	30.50
Rank	#26	Overall
	#2	Wide column stores

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

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

Technical documentation

developer.4d.com

hbase.apache.org/book.html

boilerbay.com/infinitydb/manual

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

4D, Inc

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Boiler Bay Inc.

Apache Software Foundation

Initial release

1984

2008

2002

2014

Current release

v20, April 2023

2.3.4, January 2021

4.0

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Scala

Server operating systems

OS X
Windows

Linux
Unix
Windows

using Cygwin

All OS with a Java VM

Linux
OS X
Windows

Data scheme

yes

schema-free, schema definition possible

yes

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

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

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

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

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

SQL

Support of SQL

yes

close to SQL 92

SQL-like DML and DDL statements

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Java API
RESTful HTTP API
Thrift

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

JDBC
ODBC

Supported programming languages

4D proprietary IDE
PHP

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

none

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 or Eventual Consistency

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

Single row ACID (across millions of columns)

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

Users and groups

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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More resources

DB-Engines blog posts

MySQL, PostgreSQL and Redis are the winners of the March ranking
2 March 2016, Paul Andlinger

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11 August 2021, Krishna Maheshwari (sponsor)

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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