DBMS > Blueflood vs. Brytlyt vs. LevelDB vs. OpenQM vs. SWC-DB

System Properties Comparison Blueflood vs. Brytlyt vs. LevelDB vs. OpenQM vs. SWC-DB

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

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

QpenQM is a high-performance, self-tuning, multi-value DBMS

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Time Series DBMS

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	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

blueflood.io

brytlyt.io

github.com/google/leveldb

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.brytlyt.io

github.com/google/leveldb/blob/main/doc/index.md

Developer

Rackspace

Brytlyt

Google

Rocket Software, originally Martin Phillips

Alex Kashirin

Initial release

2013

2016

2011

1993

2020

Current release

5.0, August 2023

1.23, February 2021

3.4-12

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD

Open Source

GPLv2, extended commercial license available

Open Source

GPL V3

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

C++

Server operating systems

Linux
OS X

Linux
OS X
Windows

Illumos
Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

predefined scheme

yes

schema-free

yes

with some exceptions

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

HTTP REST

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

Proprietary protocol
Thrift

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
Basic
C
Java
Objective C
PHP
Python

C++

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate 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

with automatic compression on writes

yes

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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