DBMS > Amazon Redshift vs. atoti vs. Dolt vs. FoundationDB vs. Hive

System Properties Comparison Amazon Redshift vs. atoti vs. Dolt vs. FoundationDB vs. Hive

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

Large scale data warehouse service for use with business intelligence tools

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

A MySQL compatible DBMS with Git-like versioning of data and schema

Ordered key-value store. Core features are complimented by layers.

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

Primary database model

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Secondary database models

Document store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	1.06
Rank	#185	Overall
	#31	Document stores
	#28	Key-value stores
	#85	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Website

aws.amazon.com/redshift

atoti.io

github.com/dolthub/dolt
www.dolthub.com

github.com/apple/foundationdb

hive.apache.org

Technical documentation

docs.aws.amazon.com/redshift

docs.atoti.io

docs.dolthub.com

apple.github.io/foundationdb

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

Developer

Amazon (based on PostgreSQL)

ActiveViam

DoltHub Inc

FoundationDB

Apache Software Foundation

initially developed by Facebook

Initial release

2012

2018

2013

2012

Current release

6.2.28, November 2020

3.1.3, April 2022

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2

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

C++

Java

Server operating systems

hosted

Linux
macOS
Windows

Linux
OS X
Windows

All OS with a Java VM

Data scheme

yes

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

some layers support 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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Multidimensional Expressions (MDX)

yes

supported in specific SQL layer only

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

CLI Client
HTTP REST

JDBC
ODBC
Thrift

Supported programming languages

All languages supporting JDBC/ODBC

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Python

yes

currently in alpha release

in SQL-layer only

yes

user defined functions and integration of map-reduce

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

in SQL-layer only

Transaction concepts

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

ACID

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

fine grained access rights according to SQL-standard

Only one user is configurable, and must be specified in the config file at startup

Access rights for users, groups and roles

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