DBMS > Blueflood vs. PouchDB vs. RDF4J vs. Snowflake vs. Spark SQL

System Properties Comparison Blueflood vs. PouchDB vs. RDF4J vs. Snowflake vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

JavaScript DBMS with an API inspired by CouchDB

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

Technical documentation

github.com/rax-maas/blueflood/wiki

pouchdb.com/guides

rdf4j.org/documentation

docs.snowflake.net/manuals/index.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Rackspace

Apache Software Foundation

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2013

2012

2004

2014

Current release

7.1.1, June 2019

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

JavaScript

Java

Scala

Server operating systems

Linux
OS X

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Unix
Windows

hosted

Linux
OS X
Windows

Data scheme

predefined scheme

schema-free

yes

RDF Schemas

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

yes

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

only for PouchDB Server
JavaScript API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

CLI Client
JDBC
ODBC

JDBC
ODBC

Supported programming languages

JavaScript

Java
PHP
Python

JavaScript (Node.js)
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

View functions in JavaScript

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

with a proxy-based framework, named couchdb-lounge

none

yes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

in-memory storage is supported as well

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

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.