DBMS > Blueflood vs. Brytlyt vs. HyperSQL vs. PouchDB

System Properties Comparison Blueflood vs. Brytlyt vs. HyperSQL vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Time Series DBMS

Relational DBMS

Document store

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.brytlyt.io

hsqldb.org/web/hsqlDocsFrame.html

pouchdb.com/guides

Developer

Rackspace

Brytlyt

Apache Software Foundation

Initial release

2013

2016

2001

2012

Current release

5.0, August 2023

2.7.2, June 2023

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

based on BSD license

Open Source

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

Java

C, C++ and CUDA

Java

JavaScript

Server operating systems

Linux
OS X

Linux
OS X
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

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

Data scheme

predefined scheme

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

via views

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

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

HTTP API

JDBC via HTTP
JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

All languages supporting JDBC/ODBC
Java

JavaScript

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Java, SQL

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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