DBMS > Brytlyt vs. Heroic

System Properties Comparison Brytlyt vs. Heroic

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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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Relational DBMS

Time Series DBMS

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

Score	0.45
Rank	#296	Overall
	#135	Relational DBMS

Score	0.88
Rank	#237	Overall
	#20	Time Series DBMS

Website

brytlyt.io

spotify.github.io/heroic/#!/index

Technical documentation

docs.brytlyt.io

spotify.github.io/heroic/#!/docs/overview

Developer

Brytlyt

Spotify

Initial release

2016

2014

Current release

5.0, August 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Server operating systems

Linux
OS X
Windows

Data 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 Elasticsearch

SQL

Support of SQL

yes

APIs and other access methods

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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.

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Brytlyt Releases Version 5.0, Introducing a More Intuitive, Intelligent ...
2 August 2023, Datanami

GPU Database Market Next Big Thing With Major Giants Kinetica, Omnisci, Sqream
20 September 2023, Benzinga

Brytlyt becomes NVIDIA Inception Premier Partner
31 January 2023, PR Newswire

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

Brytlyt partners with MariaDB to integrate its GPU database ...
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provided by Google News

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