DBMS > Amazon Redshift vs. FoundationDB vs. GigaSpaces vs. Heroic vs. jBASE

System Properties Comparison Amazon Redshift vs. FoundationDB vs. GigaSpaces vs. Heroic vs. jBASE

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A robust multi-value DBMS comprising development tools and middleware

Primary database model

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Multivalue DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Website

aws.amazon.com/redshift

github.com/apple/foundationdb

www.gigaspaces.com

github.com/spotify/heroic

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

Technical documentation

docs.aws.amazon.com/redshift

apple.github.io/foundationdb

docs.gigaspaces.com/latest/landing.html

spotify.github.io/heroic

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

Developer

Amazon (based on PostgreSQL)

FoundationDB

Gigaspaces Technologies

Spotify

Rocket Software (formerly Zumasys)

Initial release

2012

2013

2000

2014

1991

Current release

6.2.28, November 2020

15.5, September 2020

5.7

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

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++

Java, C++, .Net

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux
macOS
Solaris
Windows

AIX
Linux
Windows

Data scheme

yes

schema-free

some layers support schemas

schema-free

Typing

predefined data types such as float or date

yes

some layers support typing

yes

optional

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.

XML can be used for describing objects metadata

yes

Secondary indexes

restricted

yes

via Elasticsearch

SQL

Support of SQL

yes

does not fully support an SQL-standard

supported in specific SQL layer only

SQL-99 for query and DML statements

Embedded SQL for jBASE in BASIC

APIs and other access methods

JDBC
ODBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
C++
Java
Python
Scala

.Net
Basic
Jabbascript
Java

Server-side scripts

Stored procedures

user defined functions

in Python

in SQL-layer only

yes

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

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

Role-based access control

Access rights can be defined down to the item level

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