DBMS > FoundationDB vs. Hawkular Metrics vs. ITTIA vs. Riak TS

System Properties Comparison FoundationDB vs. Hawkular Metrics vs. ITTIA vs. Riak TS

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Edge Time Series DBMS with Real-Time Stream Processing

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Time Series DBMS

Secondary database models

Relational DBMS

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

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.44
Rank	#267	Overall
	#23	Time Series DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Website

github.com/apple/foundationdb

www.hawkular.org

www.ittia.com

Technical documentation

apple.github.io/foundationdb

www.hawkular.org/hawkular-metrics/docs/user-guide

www.tiot.jp/riak-docs/riak/ts/latest

Developer

FoundationDB

Community supported by Red Hat

ITTIA L.L.C.

Open Source, formerly Basho Technologies

Initial release

2013

2014

2007

2015

Current release

6.2.28, November 2020

8.7

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

Open Source

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

C++

Java

C and C++

Erlang

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
OS X

Data scheme

schema-free

some layers support schemas

schema-free

Fixed schema

schema-free

Typing

predefined data types such as float or date

some layers support typing

yes

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

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

yes

restricted

SQL

Support of SQL

supported in specific SQL layer only

yes

yes, limited

APIs and other access methods

HTTP REST

JDBC
ODBC
RESTful HTTP API
WebSocket

HTTP API
Native Erlang Interface

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Go
Java
Python
Ruby

C
C++
JavaScript (Node.js)
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

in SQL-layer only

yes

Erlang

Triggers

yes

via Hawkular Alerting

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

links between datasets can be stored

Transaction concepts

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

ACID

yes

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

Database file passwords

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