DBMS > BigchainDB vs. BoltDB vs. Drizzle vs. FatDB vs. Heroic

System Properties Comparison BigchainDB vs. BoltDB vs. Drizzle vs. FatDB vs. Heroic

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

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

An embedded key-value store for Go.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

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

Primary database model

Document store

Key-value store

Relational DBMS

Document store
Key-value store

Time Series DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Website

www.bigchaindb.com

github.com/boltdb/bolt

github.com/spotify/heroic

Technical documentation

bigchaindb.readthedocs.io/en/latest

spotify.github.io/heroic

Developer

Drizzle project, originally started by Brian Aker

FatCloud

Spotify

Initial release

2016

2013

2008

2012

2014

Current release

7.2.4, September 2012

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

MIT License

Open Source

GNU GPL

commercial

Open Source

Apache 2.0

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

C++

Java

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

via Elasticsearch

SQL

Support of SQL

yes

with proprietary extensions

Via inetgration in SQL Server

APIs and other access methods

CLI Client
RESTful HTTP API

JDBC

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

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

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C
C++
Java
PHP

Server-side scripts

Stored procedures

yes

via applications

Triggers

hooks for callbacks inside the server can be used.

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication
Source-replica replication

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

yes

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Can implement custom security layer via applications

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