DBMS > 4D vs. Datomic vs. Hive vs. Hypertable

System Properties Comparison 4D vs. Datomic vs. Hive vs. Hypertable

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Application development environment with integrated database management system

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

data warehouse software for querying and managing large distributed datasets, built on Hadoop

An open source BigTable implementation based on distributed file systems such as Hadoop

Primary database model

Relational DBMS

Wide column store

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Website

www.4d.com

www.datomic.com

hive.apache.org

Technical documentation

developer.4d.com

docs.datomic.com

cwiki.apache.org/confluence/display/Hive/Home

Developer

4D, Inc

Cognitect

Apache Software Foundation

initially developed by Facebook

Hypertable Inc.

Initial release

1984

2012

2009

Current release

v20, April 2023

1.0.6735, June 2023

3.1.3, April 2022

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2

Open Source

GNU version 3. Commercial license available

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, Clojure

Java

C++

Server operating systems

OS X
Windows

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

Data scheme

yes

schema-free

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

restricted

only exact value or prefix value scans

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

RESTful HTTP API

JDBC
ODBC
Thrift

C++ API
Thrift

Supported programming languages

4D proprietary IDE
PHP

Clojure
Java

C++
Java
PHP
Python

C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

user defined functions and integration of map-reduce

Triggers

yes

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

But extensive use of caching in the application peers

selectable replication factor

selectable replication factor on file system level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

Users and groups

Access rights for users, groups and roles

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