DBMS > Apache Druid vs. BigchainDB vs. CouchDB vs. Snowflake vs. Valentina Server

System Properties Comparison Apache Druid vs. BigchainDB vs. CouchDB vs. Snowflake vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Cloud-based data warehousing service for structured and semi-structured data

Object-relational database and reports server

Primary database model

Relational DBMS
Time Series DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

bigchaindb.readthedocs.io/en/latest

docs.couchdb.org/en/stable

docs.snowflake.net/manuals/index.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Apache Software Foundation and contributors

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Snowflake Computing Inc.

Paradigma Software

Initial release

2012

2016

2005

2014

1999

Current release

29.0.1, April 2024

3.3.3, December 2023

5.7.5

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

AGPL v3

Open Source

Apache version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Python

Erlang

Server operating systems

Linux
OS X
Unix

Linux

Android
BSD
Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

CLI Client
RESTful HTTP API

RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Haskell
Java
JavaScript
Python
Ruby

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

JavaScript (Node.js)
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

improved architecture with release 2.0

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

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.

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

yes

Access rights for users can be defined per database

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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