DBMS > Bangdb vs. Datomic vs. FoundationDB vs. Postgres-XL

System Properties Comparison Bangdb vs. Datomic vs. FoundationDB vs. Postgres-XL

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

Converged and high performance database for device data, events, time series, document and graph

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

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	0.97
Rank	#191	Overall
	#32	Document stores
	#28	Key-value stores
	#87	Relational DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Website

bangdb.com

www.datomic.com

github.com/apple/foundationdb

www.postgres-xl.org

Technical documentation

docs.bangdb.com

docs.datomic.com

apple.github.io/foundationdb

www.postgres-xl.org/documentation

Developer

Sachin Sinha, BangDB

Cognitect

FoundationDB

Initial release

2012

2013

2014

since 2012, originally named StormDB

Current release

BangDB 2.0, October 2021

1.0.7180, July 2024

6.2.28, November 2020

10 R1, October 2018

License

Commercial or Open Source

Open Source

BSD 3

commercial

limited edition free

Open Source

Apache 2.0

Open Source

Mozilla public license

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, C++

Java, Clojure

C++

Server operating systems

Linux

All OS with a Java VM

Linux
OS X
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

supported in specific SQL layer only

yes

distributed, parallel query execution

APIs and other access methods

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C#
C++
Java
Python

Clojure
Java

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

Transaction Functions

in SQL-layer only

user defined functions

Triggers

yes, Notifications (with Streaming only)

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

But extensive use of caching in the application peers

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

none

But extensive use of caching in the application peers

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

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, run db with in-memory only mode

yes

recommended only for testing and development

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

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