DBMS > Brytlyt vs. Hawkular Metrics vs. HEAVY.AI

System Properties Comparison Brytlyt vs. Hawkular Metrics vs. HEAVY.AI

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Editorial information provided by DB-Engines

Name

Description

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

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.29
Rank	#275	Overall
	#128	Relational DBMS

Score	0.02
Rank	#346	Overall
	#30	Time Series DBMS

Score	1.48
Rank	#146	Overall
	#70	Relational DBMS

Website

www.brytlyt.com

www.hawkular.org

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

Technical documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.heavy.ai

Developer

Brytlyt

Community supported by Red Hat

HEAVY.AI, Inc.

Initial release

2016

2014

2016

Current release

0.9, October 2016

5.10, January 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

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

C, C++ and CUDA

Java

C++ and CUDA

Server operating systems

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

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

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

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

HTTP REST

JDBC
ODBC
Thrift
Vega

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Go
Java
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Round robin

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

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

More information provided by the system vendor

Specific characteristics

Optimizes memory and compute layers to deliver unprecedented performance. Natively...
» more

Competitive advantages

Only HEAVY.AI allows users to visually and interactively discover high-value patterns,...
» more

Typical application scenarios

Advanced analytics, geospatial and time-series analytics, accelerated data science,...
» more

Licensing and pricing models

HEAVY.AI Free (Free Forever), Foundations ($2k/month), and Enterprise Licensure (Inquire...
» more

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More resources

Recent citations in the news

Brytlyt secures $5m for GPU-powered analytics database
22 December 2021, UKTN (UK Technology News

Brytlyt Unleashes Serverless GPU-Acceleration for Analytics
15 September 2021, PR Newswire UK

GPU Database: Market 2022 Outlook by Market Entry Strategies, Countermeasures of Economic Impact & Forecast by 2028 with Top Players | HeteroDB, Blazegraph, Graphistry, SQream – Shanghaiist
4 August 2022, Shanghaiist

GPU-accelerated data analytics startup Brytlyt raises $5M
22 December 2021, SiliconANGLE News

GPU Database Market Share, Key Dynamics 2022 Global Growth Insights, Key Players Analysis, Industry Segmentation, Latest Technologies and Emerging Trends Forecast to 2029
25 July 2022, Digital Journal

provided by Google News

The insideBIGDATA IMPACT 50 List for Q3 2022
19 July 2022, insideBIGDATA

HEAVY.AI Introduces New Capabilities that Enable Organizations to Gain Faster Access to Rapidly Growing Data Sets and Deliver Decision-Quality Information
23 March 2022, insideBIGDATA

OmniSci Gets HEAVY New Name and New CEO
1 March 2022, Datanami

The insideBIGDATA IMPACT 50 List for Q2 2022
27 April 2022, insideBIGDATA

The insideBIGDATA IMPACT 50 List for Q1 2022
10 January 2022, insideBIGDATA

provided by Google News

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