DBMS > Blueflood vs. HEAVY.AI vs. Newts vs. Quasardb

System Properties Comparison Blueflood vs. HEAVY.AI vs. Newts vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Time Series DBMS based on Cassandra

Distributed, high-performance timeseries database

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

blueflood.io

github.com/heavyai/heavydb
www.heavy.ai

opennms.github.io/newts

quasar.ai

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.heavy.ai

github.com/OpenNMS/newts/wiki

doc.quasar.ai/master

Developer

Rackspace

HEAVY.AI, Inc.

OpenNMS Group

quasardb

Initial release

2013

2016

2014

2009

Current release

5.10, January 2022

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++ and CUDA

Java

C++

Server operating systems

Linux
OS X

Linux

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Data scheme

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

HTTP REST

JDBC
ODBC
Thrift
Vega

HTTP REST
Java API

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

Java

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Round robin

Sharding

based on Cassandra

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

selectable replication factor

based on Cassandra

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

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 LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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