DBMS > BigchainDB vs. FatDB vs. Graph Engine vs. InfinityDB

System Properties Comparison BigchainDB vs. FatDB vs. Graph Engine vs. InfinityDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

A Java embedded Key-Value Store which extends the Java Map interface

Primary database model

Document store

Document store
Key-value store

Graph DBMS
Key-value store

Key-value store

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Website

www.bigchaindb.com

www.graphengine.io

boilerbay.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

www.graphengine.io/docs/manual

boilerbay.com/infinitydb/manual

Developer

FatCloud

Microsoft

Boiler Bay Inc.

Initial release

2016

2012

2010

2002

Current release

4.0

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

MIT License

commercial

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

Python

.NET and C

Java

Server operating systems

Linux

Windows

.NET

All OS with a Java VM

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

Via inetgration in SQL Server

APIs and other access methods

CLI Client
RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

RESTful HTTP API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
F#
Visual Basic

Java

Server-side scripts

Stored procedures

yes

via applications

yes

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

yes

Can implement custom security layer via applications

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More resources

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